75 research outputs found

    New challenge of the public buildings: nZEB findings from IEE RePublic_ZEB Project

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    Nearly Zero-Energy Buildings (nZEBs) have received increased attention in recent years as a result of constant concerns for energy supply constraints, decreasing energy resources, increasing energy costs and rising impact of greenhouse gases on world climate. The EPBD recast directive [1] requests all new buildings to meet higher levels of performance than before, by exploring more the alternative energy supply systems available locally on a cost-efficiency basis and without prejudicing the occupants’ comfort. To this end, after 2020, all new buildings should become “nearly zero-energy” and after 31 December 2018, the same requirement is applied for new buildings occupied and owned by public authorities. Furthermore, the EPBD recast states that MS must ensure that minimum energy performance requirements for buildings are set with a view to achieving cost-optimal levels according to the Commission Delegated Regulation (EU) No 244/2012 of 16 January 2012. In this context, the authors of this paper, who are participants in the recent started European project RePublic_ZEB, are willing to share the initial findings from on- going research work. Public buildings constitute a specific class of buildings that require a complex analysis from the statistic point of view taking into consideration the definition and typologies and other specific parameters related with. Thus, this paper will focus on the analysis of public building stocks in the countries covered by the project consortium with the view to define relevant parameters characterizing the reference public buildings that will be considered in the further analysis regarding the assessment of cost-effective packages of solutions towards nZEB levels of performance. A review of nZEB holistic approach, definitions and existing implemented policies in the participant countries, will be presented as well

    Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

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    A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe

    Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

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    A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer

    Immune stress in late pregnant rats decreases length of gestation and fecundity, and alters later cognitive and affective behaviour of surviving pre-adolescent offspring

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    Immune challenge during pregnancy is associated with preterm birth and poor perinatal development. The mechanisms of these effects are not known. 5α-Pregnan-3α-ol-20-one (3α,5α-THP), the neuroactive metabolite of progesterone, is critical for neurodevelopment and stress responses, and can influence cognition and affective behaviours. To develop an immune challenge model of preterm birth, pregnant Long–Evans rat dams were administered lipopolysaccharide [LPS; 30 μg/kg/ml, intraperitoneal (IP)], interleukin-1β (IL-1β; 1 μg/rat, IP) or vehicle (0.9% saline, IP) daily on gestational days 17–21. Compared to control treatment, prenatal LPS or IL-1β reduced gestational length and the number of viable pups born. At 28–30 days of age, male and female offspring of mothers exposed to prenatal IL-1β had reduced cognitive performance in the object recognition task compared to controls. In females, but not males, prenatal IL-1β reduced anxiety-like behaviour, indicated by entries to the centre of an open field. In the hippocampus, progesterone turnover to its 5α-reduced metabolites was lower in prenatally exposed IL-1β female, but not in male offspring. IL-1β-exposed males and females had reduced oestradiol content in hippocampus, medial prefrontal cortex and diencephalon compared to controls. Thus, immune stress during late pregnancy reduced gestational length and negatively impacted birth outcomes, hippocampal function and central neurosteroid formation in the offspring

    Evaluation of the prognostic role of centromere 17 gain and HER2/topoisomerase II alpha gene status and protein expression in patients with breast cancer treated with anthracycline-containing adjuvant chemotherapy: pooled analysis of two Hellenic Cooperative Oncology Group (HeCOG) phase III trials

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    Regional and environmental effects of the EU enlargement and Euro zone

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    Awareness of regional economic disparities has been long established. It is clear that regional disparities still play an important role in quality of life. Particularly in Europe and in the European Union, extensive research has been boosted on regional disparities and how they are influenced by the economic integration and the Economic Monetary Union. This paper proposes a theoretical framework for regional classifications and rankings based on the development of environmental indices. This framework is being used to classify European Union countries according to the extent to which they are influenced by supplyside (producer) and demand-side (consumer) responses to their specific bundle of economic and environmental attributes. This classification provides information about the relative attractiveness to producers and consumers of the combination of economic and environmental attributes indigenous to each region. It can also assist on the regional and environmental policies of the European Union by proposing an appropriate mix of environmental and regional policies for each country under examination based on a number of characteristics (high productivity, low productivity, high amenity, low amenity)

    Regional and environmental effects of the EU enlargement and Euro zone

    Full text link
    Awareness of regional economic disparities has been long established. It is clear that regional disparities still play an important role in quality of life. Particularly in Europe and in the European Union, extensive research has been boosted on regional disparities and how they are influenced by the economic integration and the Economic Monetary Union. This paper proposes a theoretical framework for regional classifications and rankings based on the development of environmental indices. This framework is being used to classify European Union countries according to the extent to which they are influenced by supply-side (producer) and demand-side (consumer) responses to their specific bundle of economic and environmental attributes. This classification provides information about the relative attractiveness to producers and consumers of the combination of economic and environmental attributes indigenous to each region. It can also assist on the regional and environmental policies of the European Union by proposing an appropriate mix of environmental and regional policies for each country under examination based on a number of characteristics (high productivity, low productivity, high amenity, low amenity).
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