Background: Surfactants are widely used across the globe both in industrial and consumer products. The n-octanol/ water partition ratio or coefficient (log K ow) and n-octanol/water distribution coefficient (log D) are key parameters in environmental risk assessment of chemicals as they are often used to estimate the environmental fate and bioavailability and thus exposure and toxicity of a compound. Determining log K ow data for surfactants is a technical challenge due to their amphiphilic properties. Currently several existing experimental OECD methods (e.g. slow-stirring, HPLC, solubility ratio) and QSPR models are available for log K ow /D measurement or prediction. However, there are concerns that these methods have not been fully validated for surfactants and may not be applicable due to the specific phase behaviour of surfactants. Results: The current methods were evaluated for the four surfactant classes (non-ionic, anionic, cationic and amphoteric). The solubility ratio approach, based on comparative n-octanol and water solubility measurements, did not generate robust or accurate data. The HPLC method generates consistently higher log K ow values than the slowstirring method for non-ionics, but this positive bias could be removed using reference surfactants with log K ow values determined using the slow-stirring method. The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the surface-active test compounds. Generally, QSPR-predicted log K ow /D values do not correlate well with experimental values, apart for the group of non-ionic surfactants. Relatively, large differences in predicted log K ow /D values were observed when comparing various QSPR models, which were most noticeable for the ionised surfactants. Conclusions: The slow-stirring method is the most widely applicable experimental method for generating log K ow /D data for all the four surfactant classes. A weight of evidence approach is considered appropriate for non-ionic surfactants using experimental and model predications. However, it is more difficult to apply this approach to ionisable surfactants. Recommendations are made for the preferred existing QSPR predictive methods for determination of log K ow /D values for the surfactant classes. Investigation of newer alternative experimental log K ow methods as well
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 ERASM (www.erasm.org). The study builds on a similar project executed by CEFIC-Franklin (1994) and summarised 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 dataset 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 were used. For worldwide traded precursor materials like palm oil, palm kernel oil, and coconut oil, an extensive literaturebased LCI study was performed. Two independent external reviewers supported the project from the beginning through completion. In addition, the oil palm and coconut-and tallowbased 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 12 companies. 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 analysed 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 optimised 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 CO 2 e/tonne for Coconut Oil Methyl Ester to 4894 kg CO 2 e/tonne for DMAPA. For the final surfactants, the range is from − 887 kg CO 2 e/tonne for CDEA to 2674 kg CO 2 e/tonne for C12-C15 AE3. There is a significant difference between the cradle-to-gate GWP of the renewable precursors palm oil/palm kernel oil (PO/PKO) and coconut oil (CNO). The CNO products have a calculated net negative cradle-to-g...
Ynediamine 1 is a versatile synthon in heterocyclic chemistry. It reacts with arylisocyanates to furnish new diaminoquinolones 4 and 5 by rearrangement as confirmed by X-Ray measurements. thyl chloride whereby an oxazolone ring is formed. measured of which 688, with I > 2.5a(I), were used in tho structure determination by MULTAN 80') and refinement (SHELX 766). Hydrogen atoms positions were calculated by the SHELX progr~mne.X-ray data of 4 can be resumed as follows t Cl3Hl7N3O, Hr -231.3, tetra-The intensity data were recorded on a Syntex PZ1 diffractomter using gra-1160 reflection8 wereThe final R value is 0.055.-8 6 9 -
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