Abstract:This research analyses the differences in impact assessment results depending on the choice of a certain software-database combination. Six packaging systems were modelled in three software-database combinations (GaBi database in GaBi software, ecoinvent 3.6 database in openLCA, Environmental Footprint database in openLCA). The chosen Life Cycle Impact Assessment (LCIA) method is EF 2.0. Differences and errors in the implementation of the LCIA method are a possible source of deviations. We compared the published characterisation factors with the factors implemented in the software-database combinations. While results for the climate change category are similar between the different databases, this is not the case for the other impact categories. In most cases, the use of the ecoinvent 3.6 database leads to higher results compared to GaBi. This is partly due to the fact, that ecoinvent datasets often include more background processes than the corresponding GaBi datasets. We found striking discrepancies in LCIA implementation, including the lack of regionalisation for water use in ecoinvent. A meaningful communication of LCIA results requires an excellent knowledge of the analysed product system, as well as of database quality issues and LCIA methodology. We fully acknowledge the constant efforts of database providers to improve their databases.Keywords: packaging; life cycle assessment; databases; life cycle impact assessment; ecoinvent; GaBi; environmental footprint database
Targeted 16S sequencing libraries were prepared using Ion 16S Metagenomics Kit (Life Technologies, Carlsbad, USA) in combination with Ion Plus Fragment Library kit (Life Technologies, Carlsbad, USA) and loaded on a 530 chip and sequenced using the Ion Torrent S5 system (Life Technologies, Carlsbad, USA). The protocol was designed for microbiome analysis using Ion torrent 510/520/530 Kit-chef template preparation system (Life Technologies, Carlsbad, USA) and included two primer sets that selectively amplified seven hypervariable regions (V2, V3, V4, V6, V7, V8, V9) of the 16S gene. At least 10 ng of total DNA was used for 16S library preparation and re-amplified using Ion Plus Fragment Library kit for reaching the minimum template concentration. Equimolar pool of libraries were estimated using Agilent High Sensitivity DNA chip (Agilent Technologies, CA, USA). Library preparation and 16S sequencing was performed with the technological infrastructure of the Centre for Omic Sciences (COS).
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Adverse health effects due to environmental chemical exposure in utero and during early life have been raised as a concern in epidemiologic studies. Neonates and infants are particularly vulnerable because of their rapid growth, cell differentiation, immaturity of metabolic pathways, and development of vital organ systems (Eskenazi et al. 1999; Landrigan et al. 1999). Neurodevelopmental effects of early-life exposure to p,p'-DDT [2,2-bis(p-chlorophenyl)-l,l,l-trichloroethane] are among the most sensitive outcomes (Agency for Toxic Substances and Disease Registry 2000). Early-life exposure to p,p' DDT was associated with a decrease in cognitive skills among preschoolers at 4 years of age (Ribas-Fito et al. 2006) and with neurobehavioral dysfunction as well as impairment of mental capacities in school age children. (Dorner and Plagemann 2002; Hardell et al. 2002). Experimental studies have shown that p,p'-DDT enhances oxidative stress and lipid peroxidation in various tissues (Koner et al. 1998; Sahoo et al. 2000). The brain is particularly susceptible to free radical-mediated insult because of its inherent bio-chemical and physiologic characteristics, including high lipid content and energy requirements (Pajovic et al. 2003). Reactive oxygen species are generated continuously in nervous tissue during normal metabolism and neuronal activity.
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