Publication - Life cycle ecofootprinting (SLE)
23 Aug 2017

New and updated life cycle inventories for surfactants used in European detergents: summary of the ERASM surfactant life cycle and ecofootprinting project

Schowanek, D. et al., Int. J . LCA, 2017

Abstract

Purpose Cradle-to-gate life cycle inventories (LCIs) for the production of a series of common surfactants used in European detergents and personal care products have been voluntarily compiled by 14 major companies collaborating within ER ASM (www.erasm.org). The study builds on a similar project executed by CEFIC-Franklin (1994) and summarized by Stalmans et al. (Tenside Surf Det 32:84–109, 1995). The data are targeted as an industry-agreed and representative market average for surfactants in Europe for the reference year 2011. The purpose of this paper is to describe how these data set were generated, to provide some summary results and interpretation, and to indicate where the full datasets and additional technical documentation can be found.

 

Methods

The methodology followed was an attributional life cycle assessment (LCA) approach, compliant with LCA standards ISO 14040 (2006), ISO 14044 (2006), and ILCD entry level (2010). For each major unit process in the production of surfactants and precursors, a minimum of three companies (a ‘trio’) was identified. When no industry-specific data were available, either literature or recent and reliable process data available, either literature or recent and reliable process data were used. For worldwide traded precursor materials like palm oil, palm kernel oil, and coconut oil, an extensive literature-based LCI study was performed. Two independent external reviewers supported the project from the beginning through completion. In addition, the oil palm and coconut- and tallow-based renewable precursors were reviewed by a third independent expert.

 

Results and discussion

In the study, a good level of representativeness was achieved with 70 primary data collections in 12companies. To illustrate the outcome of the work, two indicators/impacts were calculated and reported, i.e. primary energy demand (PED) and global warming potential (GWP). The LCIs allow the calculation of additional impact categories, but these were not analyzed within the scope of this project.

The PED for most of the surfactants and their precursors is in the range of 52 to 77 GJ/tonne. Exceptions are the production of cocamide diethanolamine (CDEA) and C16–C18 triethanolamine esterquat (TEA-quat) with a PED of around 40 GJ/tonne, and 3-dimethylaminopropylamine (DMAPA) around 108 GJ/tonne. Petrochemical precursors show an intensive but established and optimized supply chain. Where comparison is possible, their PED does not differ much from the earlier CEFIC-Franklin (1994) data. There are indications that PED for surfactant production has decreased slightly over the last 20 years due to energy efficiency measures.

The GWP for the reportable precursors ranges from− 1989 kg CO2e /tonne for Coconut Oil Methyl Ester to 4894 kg CO2e/tonne for DMAPA. For the final surfactants, the range is from − 887 kg CO2e/tonne for CDEA to 2674 kg CO2e/tonne for C12–C15 AE3. There is a significant difference between the cradle-to-gate GWP of the renewable pre-cursors palm oil/palm kernel oil (PO/PKO) and coconut oil (CNO). The CNO products have a calculated net negative cradle-to-gate GWP, while the PO/PKO products have a net

positive GWP. The latter is mainly attributable to the land use change (LUC) factor and plantings on peat soils. Beef tallow also has a net negative GWP of − 1529 kg CO2e/tonne. This value is very sensitive to the allocation choice.

Conclusions

The industry average LCI data and linked meta-data are made publically available as aggregated datasets in three different formats (EcoSpold v.2, IL CD, and GaBi 6 2013). They benefit from increased methodological standardisation and a more complete background process data versus the CEFIC-Franklin (1994) study, but are therefore only partially comparable. It is recommended that the surfactant LCI data are used and interpreted in a finished product cradle-to-grave context.

 

The paper can be found here.