Human health impacts for renewable energy scenarios from the EnerGEO Platform of Integrated Assessment (PIA)

This article reports impact results from running the EnerGEO Platform of Integrated Assessment (PIA) related to human health for different scenarios in Europe. The scenarios were prepared within the EnerGEO project. The idea of this European project is to determine how low carbon scenarios, and in particular scenarios with a high share of renewable energy, affect concentrations of air pollutants and as a consequence affect human health. PM2.5 concentrations were estimated with the IIASA Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model on a time horizon up to the year 2050 for different scenarios. We analyse here the estimation of the Loss of Life Expectancy due to PM2.5 concentrations for the Baseline scenario taken as a reference and the Maximum renewable power scenario

The EnerGEO Platform of Integrated Assessment (PIA): Environmental assessment of scenarios as a web service

With the International Energy Agency estimating that global energy demand will increase between 40 and 50 percent by 2030 (compared to 2003), scientists and policymakers are concerned about the sustainability of the current energy system and what environmental pressures might result from the development of future energy systems. EnerGEO is an ongoing FP7 Project (2009-2013) which assesses the current and future impact of energy use on the environment by linking environmental observation systems with the processes involved in exploiting energy resources. The idea of this European project is to determine how low carbon scenarios, and in particular scenarios with a high share of renewable electricity, affect emissions of air pollutants and greenhouse gases (GHG) and contribute to mitigation of negative energy system impacts on human health and ecosystems. A Platform of Integrated Assessment (PIA) has been elaborated to provide impact results for a selection of scenarios via a set of models (large-scale energy models, Life Cycle Assessment models, ...). This PIA is currently available through a web service. The concept of the PIA is detailed and to illustrate its interest, a set of results is given with the use of the simulation mode of the European version of GAINS for a selection of scenarios

Laser Scanner Demonstration

In the Summer of 2004 a request for proposals went out to potential vendors to offer a three-dimensional laser scanner for a number of unique metrology tasks at the Stanford Linear Accelerator Center (SLAC). Specifications were established including range, accuracy, scan density, resolution and field of view in consideration of anticipated department requirements. Four vendors visited the site to present their system and they were asked to perform three unique tests with their system on a two day visit to SLAC. Two of the three tests were created to emulate real-world applications at SLAC while the third was an accuracy and resolution series of experiments. The scope of these tests is presented and some of the vendor's results are included

Thorium nanochemistry: The solution structure of the Th(iv)-hydroxo pentamer

Tetravalent thorium exhibits a strong tendency towards hydrolysis and subsequent polymerization. Polymeric species play a crucial role in understanding thorium solution chemistry, since their presence causes apparent solubility several orders of magnitude higher than predicted by thermodynamic data bases. Although electrospray mass spectrometry (ESI MS) identifies Th(iv) dimers and pentamers unequivocally as dominant species close to the solubility limit, the molecular structure of Th 5(OH) y polymers was hitherto unknown. In the present study, X-ray absorption fine structure (XAFS) spectroscopy, high energy X-ray scattering (HEXS) measurements, and quantum chemical calculations are combined to solve the pentamer structure. The most favourable structure is represented by two Th(iv) dimers linked by a central Th(iv) cation through hydroxide bridges. © 2012 The Royal Society of Chemistry

The Relationship Between the Number of Shots and the Quality of Gamma Knife Radiosurgeries

Radiosurgery is a non-invasive alternative to brain surgery that uses a single focused application of high radiation to destroy intracerebral target tissues. A Gamma Knife delivers such treatments by using 201 cylindrically collimated cobalt-60 sources that are arranged in a hemispherical pattern and aimed to a common focal point. The accumulation of radiation at the focal point, called a \shot due to the spherical nature of the dose distribution, is used to ablate (or destroy) target tissue in the brain. If the target is small and spherical, it is easily treated by choosing one of four available collimators (4, 8, 14, or 18 mm). For large, irregular targets, multiple shots are typically required to treat the entire lesion, and the process of determining the optimal arrangement and number of shots is complex. In this research, fast simulated annealing and a novel objective function are used to investigate the relationship between the number of shots and the quality of the resulting treatment. Sets of 5, 10, 25, 50, and an unrestricted number of shots are studied for an arteriovenous malformation (AVM). As the shot limit increases the following improvements in plan quality are observed: the conformity of the prescription isodose line increases, the lesion dose becomes more homogeneous, and an increase use of smaller collimators to deposit dose. Large improvements in plan quality are realized by increasing the number of shots from 5 to 50, and to achieve a similar magnitude of improvement past 50 requires an increase over 1500 shots for the complex lesion investigated. This observation suggests that it is clinically valuable to improve the Gamma Knife\u27s delivery capabilities so that 50 shot treatments are possible

Genetic and environmental influences on eating behavior - a study of twin pairs reared apart or reared together

This study examined the relative influence of genetic versus environmental factors on specific aspects of eating behavior. Adult monozygotic twins (22 pairs and 3 singleton reared apart, 38 pairs and 9 singleton reared together, age 18-76 years, BMI 17-43 kg/m2) completed the Three Factor Eating Questionnaire. Genetic and environmental variance components were determined for the three eating behavior constructs and their subscales using model-fitting univariate and multivariate analyses. Unique environmental factors had a substantial influence on all eating behavior variables (explaining 45-71% of variance), and most strongly influenced external locus for hunger and strategic dieting behavior of restraint (explaining 71% and 69% of variance, respectively). Genetic factors had a statistically significant influence on only 4 variables: restraint, emotional susceptibility to disinhibition, situational susceptibility to disinhibition, and internal locus for hunger (heritabilities were 52%, 55%, 38% and 50%, respectively). Common environmental factors did not statistically significantly influence any variable assessed in this study. In addition, multivariate analyses showed that disinhibition and hunger share a common influence, while restraint appears to be a distinct construct. These findings suggest that the majority of variation in eating behavior variables is associated with unique environmental factors, and highlights the importance of the environment in facilitating specific eating behaviors that may promote excess weight gain.R01 AR046124 - NIAMS NIH HHS; R01 MH065322 - NIMH NIH HHS; T32 HL069772 - NHLBI NIH HHS; R37 DA018673 - NIDA NIH HHS; R01 DK073321 - NIDDK NIH HHS; R01 DA018673 - NIDA NIH HH

Effect of body composition methodology on heritability estimation of body fatness

Heritability estimates of human body fatness vary widely and the contribution of body composition methodology to this variability is unknown. The effect of body composition methodology on estimations of genetic and environmental contributions to body fatness variation was examined in 78 adult male and female monozygotic twin pairs reared apart or together. Body composition was assessed by six methods - body mass index (BMI), dual energy x-ray absorptiometry (DXA), underwater weighing (UWW), total body water (TBW), bioelectric impedance (BIA), and skinfold thickness. Body fatness was expressed as percent body fat, fat mass, and fat mass/height2 to assess the effect of body fatness expression on heritability estimates. Model-fitting multivariate analyses were used to assess the genetic and environmental components of variance. Mean BMI was 24.5 kg/m2 (range of 17.8-43.4 kg/m2). There was a significant effect of body composition methodology (p<0.001) on heritability estimates, with UWW giving the highest estimate (69%) and BIA giving the lowest estimate (47%) for fat mass/height2. Expression of body fatness as percent body fat resulted in significantly higher heritability estimates (on average 10.3% higher) compared to expression as fat mass/height2 (p=0.015). DXA and TBW methods expressing body fatness as fat mass/height2 gave the least biased heritability assessments, based on the small contribution of specific genetic factors to their genetic variance. A model combining DXA and TBW methods resulted in a relatively low FM/ht2 heritability estimate of 60%, and significant contributions of common and unique environmental factors (22% and 18%, respectively). The body fatness heritability estimate of 60% indicates a smaller contribution of genetic variance to total variance than many previous studies using less powerful research designs have indicated. The results also highlight the importance of environmental factors and possibly genotype by environmental interactions in the etiology of weight gain and the obesity epidemic.R01 AR046124 - NIAMS NIH HHS; R01 MH065322 - NIMH NIH HHS; T32 HL069772 - NHLBI NIH HHS; R21 DK078867 - NIDDK NIH HHS; R37 DA018673 - NIDA NIH HHS; R01 DK076092 - NIDDK NIH HHS; R01 DK079003 - NIDDK NIH HHS; F32 DK009747 - NIDDK NIH HHS; R01 DA018673 - NIDA NIH HH