Global normalisation factors for the Environmental Footprint and Life Cycle Assessment

This report quantitatively characterizes environmental impacts at global scale in relation to the 16 impact categories of the Environmental Footprint (EF) and Life Cycle Assessment (LCA), namely: climate change; ozone depletion; human toxicity, cancer; human toxicity, non-cancer; freshwater ecotoxicity; particulate matter; ionising radiation; photochemical ozone formation; acidification; eutrophication, terrestrial; eutrophication, marine; eutrophication, freshwater; land use; water use; resource use, fossils and resource use, minerals and metals. The results are recommended to be used as normalisation factors (NFs) in the context of the Environmental Footprint (EF) for assessing the relevance of the impacts associated to a product or system. In LCA, according to ISO 14044 (ISO 2006), normalisation (similar to weighting) is an optional steps of Life Cycle Impact Assessment (LCIA). The normalisation factors represent the total impact of a reference region for a certain impact category (e.g. climate change, eutrophication, etc.) in a reference year. For the EF, due to the international nature of supply chains, the use of global normalisation factors is recommended. Normalisation has a relevant role to play in the Environmental Footprint to support the identification of the most relevant impact categories, life cycle stages, process and resource consumptions or emissions to ensure that the focus is put on those aspects that matter the most and for communication purposes. The global normalisation factors reported here are built on a vast collection of data on emissions and resources extracted at global scale in 2010. Key choices were made for compiling the inventories, which were then characterised by using the EF midpoint LCIA method. The results are reported for each impact category. Coverage, completeness and robustness of the underpinning inventories are discussed. With this, the report supports the generation of life cycle based indicators for monitoring the environmental dimension of the sustainability of supply chains, including contributions to global environmental impacts in relation to planetary boundaries. This in turn enables a life cycle based assessment of the sustainability of the intensification of primary production for a greening EU economy.JRC.D.1-Bio-econom

Global environmental impacts: data sources and methodological choices for calculating normalization factors for LCA

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Structure and pattern of food consumption in Italian household: an analysis of impact on climate change and land use

The environmental impacts of food consumption of Italian households in 2011 have been calculated adopting an Environmentally Extended Input-Output Analysis, using EXIOBASE v3 as the underpinning database for the assessment. Because of the structure of such database, it is possible to divide domestic and imported final demand. Climate change and Land use related impacts are calculated then matched with household expenditures for the same year. The food consumption in an average Italian household for 2011 results in a total Climate change of 4237 kg CO2eq and in a total Land use impact of 10 kg Cdeficit. There are limitations due to a non-perfect match of food product groups in EXIOBASE and Italian National Statistics. Nevertheless, with this approach it is possible to investigate environmental impacts in relation to expenditure patterns of the families

Handedness and Mathematics: Toward a More Comprehensive Model

The relationship between handedness and mathematical abilities is controversial. Whilst some researchers haveclaimed that left-handers are gifted in mathematics and strong right-handers perform the worst in mathematical tasks, it hasbeen more recently proposed that mixed-handers are actually the most disadvantaged group. To disentangle these discrepancies,we conducted five experiments in several Italian schools (total participants: N = 2,308) involving students of different ages(6 to 17 years) and a range of mathematical tasks. The results showed that (a) the percentage of variance in mathematicsscores explained by handedness was moderate (about 5%) but statistically significant, and (b) the shape of the relationshipbetween handedness and mathematical ability depended on age, task, and gender. We concluded that the different outcomesreported in the literature probably reflected the dissimilarities between the studies about the above variables. Therefore, a morecomprehensive model is needed, which explains how these variables interact

Challenges to recruitment of participants with MCI in a multicentric neuropsychological study

Background: Data on recruitment of Mild Cognitive Impairment (MCI) samples are seldom reported and this issue can be an important source of research waste. Aim: To describe the recruitment challenges and reasons for non-eligibility faced during a bi-centre clinical study assessing the predictive value of a neuropsychological battery of the progression to dementia. Methods: Potential MCI participants were identified from databases of the two memory clinics based in Milan (Italy) and invited to the screening assessment. Results: About 50% of the cases initially identified were ineligible according to inclusion/exclusion criteria and the two sites took 22 months to recruit the planned 150 people. The main reasons for non-eligibility were the MMSE score (41%), age (14%), presence of cerebrovascular disorders (9%), perceptual deficits (6%), neurological (6%) or psychiatric (4%) comorbidities and low education (5%). Conclusion: Awareness of the reasons for exclusion and of the time needed to recruit the planned sample would provide hints for the planning of future studies on MCI

Does poor stunning affect the assessment of animal-based measures consciousness in lambs at slaughter?

Oral session 2[EN] According to EU legislation on the killing of animals (EC n. 1099/2009), to ensure that animals do not regain consciousness before slaughter, the efficiency of stunning method must be evaluated through animal-based measures (ABMs)

Supporting information to the characterisation factors of recommended EF Life Cycle Impact Assessment methods: New methods and differences with ILCD

In 2013, the Environmental Footprint methodology has been established with a specific Recommendation (2013/179/EU), within the framework of the “Single Market for Green Products” communication (COM/2013/0196). The International Life Cycle Data system, developed since 2007, released in 2010 and continuously maintained by JRC, has been adopted in the EF framework. ILCD format and nomenclature were adopted as requirements for EF. Given the different needs and goals of the EF, some methods for the Life Cycle Impact Assessment have been changed compared to ILCD (and therefore the elementary flows have been adapted accordingly, and to some extent, the format has been expanded). The the LCIA methods are developed within the database as ILCD-formatted xml files to allow electronic import into LCA software; The LCIA methods are implemented as separate data sets which contain all the descriptive metadata documentation and the characterisation factors assigned to different elementary flows (that are also xml files within the DB). This document provide a view on the changes occurred within the methods for the mid-point impact assessment (the EF is considering for now only impacts at the level of potential changes, not at the potential damage level, which was captured in ILCD scheme for the methods at the end-point level). The changes and adaptations occurred within the ILCD scheme, that led to the creation of the current EF set of methods and a new package, based on ILCD format, containing new files for LCIA methods, can be summarized as follows: • 6 methods are completely new, or updated according to the newest releases of the old methods adopted in ILCD. • The elementary flow list has been fixed and expanded according to the needs of the new methods • Within the new methods several flows have been spatially differentiated (in ILCD format the location attribute is resolved at the method level, not at the elementary flow level) • For several flows that were not characterized (both in newly added methods and in the pre-existing ones that were not modified), a CF has been adopted, where a direct proxy for a specific substance/compartment was available. • Specific exceptions, integrations or corrections have been implemented in different methods. All these aspects are detailed within the document. Furthermore, additional files have been released, containing an exhaustive view of all the changes occurred in the transition phase between the ILCD and the EF scheme (see annex2). Additional updates will be released through the website of the European Platform on LCA (http://eplca.jrc.ec.europa.eu/). Other methods (e.g. those related to toxicity aspects) are under development, during the editing of this document; therefore an updated version will be released as soon as the new recommended methods are defined.JRC.D.1-Bio-econom

Outcome of 518 salvage oocyte-cryopreservation cycles performed as a routine procedure in an in vitro fertilization program

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Electrophysiological changes of cardiac function during antidepressant treatment

Some antidepressant agents can cause electrophysiological changes of cardiac function leading to ventricular arrhythmias and sudden death. However, antidepressants have also protective effects on the heart through their capacity to modulate cardiac autonomic-mediated physiological responses. Heart rate variability and QTc length are two strictly linked parameters that allow us to appreciate the effects of different drugs on cardiac physiology. Heart rate variability reflects functioning of the autonomic nervous system and possibly also regulation by the limbic system. Autonomic regulation of cardiac activity influences also cardiac repolarization and QT length, both directly and via its effects on heart rate. In this review we present the methodologies adopted to study the effect of antidepressant drugs on QT length and heart rate variability and we summarize data on electrophysiological changes related to antidepressant treatment. Clinical implications for the choice of different antidepressants in different clinical populations are discussed