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In a previous study, we assessed the efficiency of reducing either traffic or industrial emissions on various ozone metrics for several cities in Europe, based on the Air Control Toolbox surrogate model. Here, we perform various model parametrisation sensitivity analyses in order to assess the robustness of our results. We find that increasing the model resolution has a limited impact on the ozone response to emission changes when focusing on concentration peaks but strongly changes the response of the ozone daily mean with a switch to a titration regime for all zones with significant nitrogen oxide (NOx) emissions. The impact of pollution imported from outside the simulation domain was also studied and we show that if the first lever for action on ozone peaks remains as the reduction of local and regional emissions, in order to achieve higher levels of reduction, it is necessary to act at a European level. We also explore more up-to-date temporal profiles and sectoral emission speciation and find a shift towards a more NOx-limited regime in a number of cities. Overall, these sensitivity tests show that most of the differences are simulated in cities with high NOx emissions and little solar radiation but do not change the overall conclusions that were previously obtained. [ABSTRACT FROM AUTHOR]

Using a cross section of matched data from the employee and management questionnaires of the European Company Survey for 28 nations, this paper investigates the determinants of worker commitment and the potential contribution of commitment to establishment performance. An index of worker commitment is constructed from employer perceptions of the motivation of workers and their retention and absenteeism propensities, while the determinants of commitment are fashioned from observations taken from the worker representation side, ordered along dimensions such as perceived organizational trust and involvement. The commitment index is then linked to establishment performance outcomes. Key findings from the commitment equation are the positive role of trust in management, the quality of information exchanged, and the degree of worker representation influence in respect of major decisions taken by management. In turn, commitment emerges as a key correlate of establishment financial performance and labor productivity growth. Our supplemental sensitivity analysis is supportive of the interpretation of commitment as a driver of performance. [ABSTRACT FROM AUTHOR]

The maximum latewood density (MXD) of tree rings can reflect the temperature of the growing season, but the timing of the response differs among regions. We selected 152 maximum latewood density chronologies from the Northern Hemisphere that showed a significant response to temperature. Based on a cluster analysis and the sensitivity of MXD to the monthly mean temperature, the chronologies were classified into six clusters. The clusters showed distinct regional characteristics, and the period and peak month of significant response of the chronologies in each cluster to temperature were different. Spatial synchronization of the MXDs revealed that the two clusters distributed in Europe showed the most consistency and the strongest response to the April–September monthly mean temperature compared with the other clusters. Temperature accounted for more than 40% of the total MXD variance in all clusters, whereas the effect of precipitation was much smaller. In addition to climatic factors, the random effect of the latitude and longitude of sampling sites, elevation, and tree species was a major factor contributing to the variance in MXD in each cluster. Latitude and longitude had the strongest influence among the three random effects, and tree species had the weakest influence, except at high latitudes. The MXD of each cluster showed sensitivity to temperature within a certain interval, with a positive linear response, and the sensitivity interval was greatest at high latitudes. Certain clusters showed a negative linear sensitivity to precipitation. The results provide a reference for studying the climatic threshold of large-scale tree-ring density formation. [ABSTRACT FROM AUTHOR]

In this paper, a simple model is proposed for predicting the thermal energy requirements of greenhouses in Europe. The model estimates the annual heating requirements and the maximum required heating power, along with the corresponding heating and zero-energy operating periods. It is based on the greenhouse technical data (the overall heat loss coefficient, cover transmission, sensible absorbance), the cultivation conditions (temperature range), and the meteorological data (solar radiation and ambient temperature) according to the site characteristics (longitude and latitude). The model results can be obtained using a hand calculator. The model results are compared with those of a detailed model simulating a greenhouse's thermal performance and they agreed with real data from the literature. Moreover, a model sensitivity analysis revealed the effect of various factors on the greenhouse's energy requirements. The results proved that the most significant factor affecting heating requirements, the maximum heating power, and heating periods is the latitude of the greenhouse site, whereas zero-energy periods are primarily influenced by the plant cultivation temperature range and then by the latitude. According to our findings, in lower latitudes (40 to 50 degrees), heating requirements range from 250 to 430 kWh/m2/y, whereas, in higher latitudes (50 to 60 degrees), heating needs range from 430 to 650 kWh/m2/y. [ABSTRACT FROM AUTHOR]

An extensive parametric study of the seismic response of one-storey precast buildings with horizontal cladding panels frequently used in Central Europe was conducted to analyse the panels' influence on the overall response of buildings and to find out if the panels can be considered non-structural elements when they are attached to the main building with the connections typically used in practice in Central Europe. The studied structural system consisted of reinforced concrete columns and beams connected by dowels. Horizontal cladding panels were attached to columns using one of the most frequently used isostatic fastening systems. The top connections provided out-of-plane stability, and the bottom connections supported the panel in the vertical direction. The parametric study was preceded by extensive experimental research, including cyclic tests on connections and full-scale shaking table tests of whole buildings. The results of experiments were used to reveal the basic response mechanisms of panels and connections and to develop, validate and calibrate numerical models employed in the parametric study presented herein. Fifteen generalised structures with different masses and heights were subjected to 30 accelerograms with two peak ground acceleration (PGA) intensities of 0.3 g and 0.5 g, corresponding to significant damage and near-collapse limit states. The effects of the construction imperfections in connections, the silicon sealant panel-to-panel connections and different types of connections of the bottom panel to the foundation were analysed. The crucial parameter influencing the response was the displacement capacity of the connections, which was considerably affected by the construction imperfections and, consequently, difficult to estimate. It has been observed that in some buildings, particularly in shorter structures with smaller mass, cladding panels can have a somewhat more notable influence on the overall response. However, in general, when the considered types of connections are used, the panels can be considered as non-structural elements, which do not importantly influence the response of the main building. Owing to structural imperfections and relatively short available gaps, the failure of the considered top connections and falling of the panels is very likely in the high seismicity regions. In the most adverse cases, it can occur even in the moderate seismicity regions. [ABSTRACT FROM AUTHOR]

This data article relates to the paper "Review of the cost-optimal methodology implementation in Member States in compliance with the Energy Performance of Buildings Directive". Datasets linked with this article refer to the analysis of the latest national cost-optimal reports, providing an assessment of the implementation of the cost-optimal methodology, as established by the Energy Performance of Building Directive (EPBD). Based on latest national reports, the data provided a comprehensive update to the cost-optimal methodology implementation throughout Europe, which is currently lacking harmonization. Datasets allow an overall overview of the status of the cost-optimal methodology implementation in Europe with details on the calculations carried out (e.g., multi-stage, dynamic, macroeconomic, and financial perspectives, included energy uses, and full-cost approach). Data relate to the implemented methodology, reference buildings, assessed cost-optimal levels, energy performance, costs, and sensitivity analysis. Data also provide insight into energy consumption, efficiency measures for residential and non-residential buildings, nearly zero energy buildings (NZEBs) levels, and global costs. The reported data can be useful to quantify the cost-optimal levels for different building types, both residential (average cost-optimal level 80 kWh/m2y for new, 130 kWh/m2y for existing buildings) and non-residential buildings (140 kWh/m2y for new, 180 kWh/m2y for existing buildings). Data outline weak and strong points of the methodology, as well as future developments in the light of the methodology revision foreseen in 2026. The data support energy efficiency and energy policies related to buildings toward the EU building stock decarbonization goal within 2050. Datasets: Data directly related to this article are provided in the Supplementary Materials. Dataset License: CC-BY 4.0. [ABSTRACT FROM AUTHOR]

Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners. [ABSTRACT FROM AUTHOR]

Europe is transitioning towards a sustainable energy economy. Planning these future power and energy systems is multifaceted and complex, requiring long-term projections of future electricity market dynamics. The prognostication of future prices is crucial for power system planning, as these prices will drive investments and impact incentives to build and improve new systems. The price of electricity in different regions impacts transmission investment. Energy systems models have high-dimensional output and are expensive to evaluate, leading to unique challenges in managing the uncertainty in model assumptions. This study presents a novel methodology for determining which cost assumptions are most impactful on the output of a detailed model of the European energy system. Because this model is computationally intensive, only a small number of samples are available to us. A multiple-output support vector regression is used as a surrogate of predicted electricity prices timeseries. We find that solar and wind costs are the primary drivers of electricity prices, but natural gas costs generally drive peak electricity prices and those far in the future. • A surrogate-based sensitivity analysis is presented for energy systems modeling. • Linear and nonlinear surrogate approaches are compared. • Nonlinear surrogate modeling is recommended in this setting. [ABSTRACT FROM AUTHOR]

Coastal flooding estimation at large scale, e.g. pan-European is usually performed using static method while dynamic method, in which numerical flood models are used to solve hydrodynamic equations, have proven to perform better. However, a numerical flood model can rapidly become computationally demanding. Thus, to respect the balance between efficiency and quality, models need to be properly configured. Usually, the model configuration is supported by calibration and validation. In the cases where it is not possible to appropriately implement calibration and validation through comparison against observed and measured data, sensitivity analyses can be applied in order to identify the key parameters that could influence the model capability to properly represent the modelled process. The present work aimed to identify influential model parameters across Europe and their relative importance in flood model configuration. Seventeen test cases were selected for which a LISFLOOD-FP model was developed, covering several sites across Europe and considering different storm events. A panoply of local morphologies and boundary conditions derived from the sites and storm event characteristics were used. For each test case, 72 simulations with different configurations were performed by varying the grid resolution, the numerical solver, the bottom friction and the wave set-up formulation used to estimate the total water level as a boundary condition. Two sensitivity analyses were performed on the modelled maximum flooded areas and water volumes using One-Driver-At-a-Time and variance-based methods. By using a k-means clustering method, the results of these sensitivity analyses allowed us to identify patterns through the test cases related to the geographical region, providing important information for the configuration of flood models across Europe. Both sensitivity analysis methods led to similar results highlighting dominant relative influences from the floodplain solver on the Atlantic coasts and from the boundary conditions on the Mediterranean ones. In addition the grid resolution was found to have great effect on the North and Baltic seas, while globally the friction was shown to impact the model's results less. The test cases were clustered using a k-means method using as input both the sensitivity analysis results and morphological factors. Depending upon the inputs, two different sets of clusters were generated revealing a complex relationship between the influence of the model's parameters and the selected morphological indicators. • 17 test cases of coastal flooding in Europe were simulated using LISFLOOD-FP model. • One-Driver-At-a-Time and variance based sensitivity analyses identified key parameter. • Significant influence of the floodplain solver, wave set-up and grid resolution. • Result models were relatively not sensitive to the friction configuration. [ABSTRACT FROM AUTHOR]

We propose a chance-constrained formulation for the problem of dimensioning frequency restoration reserves on a power transmission network. We cast our problem as a two-stage stochastic mixed integer linear program, and propose a heuristic algorithm for solving the problem. Our model accounts for the simultaneous sizing of both upward and downward reserves, and uncertainty driven by imbalances, contingencies and available transmission capacity. Our core methodology is further adapted in order to minimize inter-zonal flows and in order to split reserve requirements between automatic and manual frequency restoration reserves. We apply our methodology to the problem of sizing reserves in the four load frequency control areas of the Swedish power system. We demonstrate the benefits of our method in terms of decreasing reserve requirements in the absence of reserve sharing, we analyze the spatial allocation of reserves, and we perform various sensitivity analyses. [ABSTRACT FROM AUTHOR]

Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on expert opinion. These two methods resulted in vulnerability maps with the expert weighting showing in general higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback-relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the factors. Thus, we recommend to apply this mixed-method approach to close the gap between science and practitioners. [ABSTRACT FROM AUTHOR]

Bovine besnoitiosis (BB) is a chronic and debilitating parasitic disease in cattle caused by the protozoan parasite Besnoitia besnoiti. South European countries are affected and have reported clinical cases of BB. However, BB is considered as emerging in other countries/regions of central, eastern and northern Europe. Yet, data on drivers of emergence of BB in Europe are scarce. In this study, fifty possible drivers of emergence of BB in cattle were identified. A scoring system was developed per driver. Then, the scoring was elicited from eleven recognized European experts to: (i) allocate a score to each driver, (ii) weight the score of drivers within each domain and (iii) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order of importance. Regression tree analysis was used to group drivers with comparable likelihoods to play a role in the emergence of BB in cattle in Europe. Finally, robustness testing of expert elicitation was performed for the seven drivers having the highest probability to play a key role in the emergence of BB: i.e., (i) legal/illegal movements of live animals from neighbouring/European Union member states or (ii) from third countries, (iii) risk of showing no clinical sign and silent spread during infection and post infection, (iv) as a consequence, difficulty to detect the emergence, (v) existence of vectors and their potential spread, (vi) European geographical proximity of the pathogen/disease to the country, and (vii) animal density of farms. Provided the limited scientific knowledge on the topic, expert elicitation of knowledge, multi-criteria decision analysis, cluster and sensitivity analyses are very important to prioritize future studies, e.g., the need for quantitative import risk assessment and estimation of the burden of BB to evidence and influence policymaking towards changing (or not) its status as a reportable disease, with prevention and control activities targeting, firstly, the top seven drivers. The present methodology could be applied to other emerging animal diseases. [ABSTRACT FROM AUTHOR]

Background: Hundreds of studies on environmental effects of genetically modified (GM) crops became available over the past 25 years. For maize producing insecticidal proteins from Bacillus thuringiensis (Bt), potential adverse effects on non-target organisms are a major area of concern and addressed in risk assessments. Reviews and meta-analyses have helped various stakeholders to address uncertainties regarding environmental impacts of the technology. Many field studies from Europe and other parts of the world have been published in the last decade, and those data are often not covered by previous meta-analyses. Therefore, we conducted a systematic review to answer the question: "Does the growing of Bt maize change abundance or ecological function of non-target animals compared to the growing of non-GM maize?" Methods: Literature published until August 2019 was searched systematically in 12 bibliographic databases, 17 specialized webpages, and reference sections of 78 review articles. Defined eligibility criteria were applied to screen titles, abstracts, and full texts of the retrieved references. A custom-made database was developed with quantitative data on invertebrate abundance, activity density, or predation/parasitism rates. Eligible data that did not fit the quantitative database were captured in detailed tables and summarized narratively. For the first time, a critical appraisal scheme for field studies on non-targets in GM crops was developed to estimate the risk of bias (internal validity) and the suitability to answer the review question (external validity) of all primary data. Meta-analyses on different taxonomic levels, functional groups, and types of Bt maize were conducted. Untreated Bt maize was either compared with untreated non-Bt maize, or with insecticide-treated non-Bt maize. The influence of contributions by private sector product developers on reported effects was investigated. Review findings: The database on non-target effects of Bt maize field trials contains more than 7200 records from 233 experiments and 120 articles. Meta-analyses on different taxonomic levels revealed only few and often non-robust significant effect sizes when both Bt maize and non-Bt maize were untreated. Bt maize harboured fewer parasitoids (Braconidae, Tachinidae) of the European corn borer, the main target pest of Lepidoptera-active Bt maize, compared with non-Bt maize. Similarly, sap beetles (Nitidulidae), that are associated with Lepidoptera damage, were recorded less in Bt maize. In some analyses, a negative effect of Bt maize was observed for rove beetles (Staphylinidae) and hoverflies (Syrphidae) and a positive effect for ladybeetles (Coccinellidae), flower bugs (Anthocoridae), and lacewings (Neuroptera). However, those effects were not consistent for different analyses and often related to individual articles. When untreated Bt maize was compared with pyrethroid-treated non-Bt maize, more effect sizes were significant. In particular, populations of predators were reduced after pyrethroid treatment, while few data were available for other insecticides. Funnel plots showed no evidence for publication bias and the analyses of private sector contribution revealed no evidence for influence of vested interests. Conclusions about potential effects of Bt maize on vertebrates or on animals inhabiting off-crop habitats were not possible, because only few such studies fitting the format of direct Bt/non-Bt comparisons on plot or field level were identified. Conclusions: The current work largely confirmed previously published results. The effects of Bt maize on the community of non-target invertebrates inhabiting maize fields were small and mostly neutral, especially when compared with the effects of broad-spectrum pyrethroid insecticide treatments. [ABSTRACT FROM AUTHOR]

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the imperative of leveraging renewable indigenous energy sources becomes evident. However, as such technologies are integrated into the existing system, it is necessary to shift from the current centralized infrastructure to a decentralized production strategy. This paper presents a method to identify a panel of technological solutions at the district level, intended to reduce complexity for the integration of decentralized models into a national-scale model. The framework's novelty lies in combining a global sensitivity analysis for solution generation with clustering to identify typical configurations. The global sensitivity analysis is performed on a mixed integer linear programming model, which optimally sizes and operates district energy systems. The sensitivity analysis determines the most influential parameters of the model using the Morris method and provides a representative sampling of the solution space by leveraging the Sobol sampling strategy. The latter is then clustered using a density-based algorithm to identify typical solutions. The framework is applied to a suburban and residential Swiss neighborhood. The first outcome of the research is the high sensitivity of the model to energy carrier prices. As a result, Sobol's sampling space separates itself into two system types: those based on a natural gas boiler and those relying on a combination of electrical heaters and heat pumps. For both types, the electricity demand is either fulfilled by PV panels or electricity imports. The identified configurations showcase that the framework successfully generates a panel of solutions composed of various system configurations and operations being representative of the overall solution space. • Energy carriers' retail prices are the most influential parameters of a district energy system. • Energy system configurations differ according to the consumed energy carrier and PV penetration. • PV deployment is affected by electricity tariffs but not by technological implementations. [ABSTRACT FROM AUTHOR]

In September 2017, numerous measurement stations recorded large surface concentrations of Ru 106 in Europe. This event was well recorded by various monitoring stations worldwide and offer a valuable framework to compare the modelling strategies deployed to quickly evaluate where the plume goes and with what concentrations. In general, the source and its intensity are not known and hypotheses have to be done. Models have to be fast and accurate: Lagrangian and Eulerian are often used but rarely compared. In this study, the FLEXPART Lagrangian model and the WRF-CHIMERE Eulerian models are used to simulate the emissions, transport and deposition of this source of Ru 106. First, it is shown that the hypothesis of location, timing and intensity of the source is realistic, by comparison to surface measurements. Second, sensitivity analysis performed with the Eulerian model and several transport scheme showed that this model may provide better results than the Lagrangian one. It opens the door to further development, including chemistry and mixing with other pollutants during these specific events. • Long range atmospheric transport in CHIMERE and FLEXPART models yield similar behaviors. • Numerous worldwide measurements allowed the comparison of CHIMERE and FLEXPART at various ranges. • Confusion matrices indicate that CHIMERE performs overall better than FLEXPART on this case. • Numerical diffusion in CHIMERE can be reduced with newly implemented numerical transport schemes. • Conjoint use of both CHIMERE and FLEXPART could be beneficial in future work. [ABSTRACT FROM AUTHOR]

The influenza D virus (IDV) was first identified and characterized in 2011. Considering the virus' zoonotic potential, its genome nature (segmented RNA virus), its worldwide circulation in livestock and its role in bovine respiratory disease, an increased interest is given to IDV. However, few data are available on drivers of emergence of IDV. We first listed fifty possible drivers of emergence of IDV in ruminants and swine. As recently carried out for COVID‐19 in pets (Transboundary and Emerging Diseases, 2020), a scoring system was developed per driver and scientific experts (N = 28) were elicited to (a) allocate a score to each driver, (b) weight the drivers' scores within each domain and (c) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order. Drivers with comparable likelihoods to play a role in the emergence of IDV in ruminants and swine in Europe were grouped using a regression tree analysis. Finally, the robustness of the expert elicitation was verified. Eight drivers were ranked with the highest probability to play a key role in the emergence of IDV: current species specificity of the causing agent of the disease; influence of (il)legal movements of live animals (ruminants, swine) from neighbouring/European Union member states and from third countries for the disease to (re‐)emerge in a given country; detection of emergence; current knowledge of the pathogen; vaccine availability; animal density; and transport vehicles of live animals. As there is still limited scientific knowledge on the topic, expert elicitation of knowledge and multi‐criteria decision analysis, in addition to clustering and sensitivity analyses, are very important to prioritize future studies, starting from the top eight drivers. The present methodology could be applied to other emerging animal diseases. [ABSTRACT FROM AUTHOR]

In coastal regions, floods can arise through a combination of multiple drivers, including direct surface run-off, river discharge, storm surge, and waves. In this study, we analyse compound flood potential in Europe and environs caused by these four main flooding sources using state-of-the-art databases with coherent forcing (i.e. ERA5). First, we analyse the sensitivity of the compound flooding potential to several factors: (1) sampling method, (2) time window to select the concurrent event of the conditioned driver, (3) dependence metrics, and (4) wave-driven sea level definition. We observe higher correlation coefficients using annual maxima than peaks over threshold. Regarding the other factors, our results show similar spatial distributions of the compound flooding potential. Second, the dependence between the pairs of drivers using the Kendall rank correlation coefficient and the joint occurrence are synthesized for coherent patterns of compound flooding potential using a clustering technique. This quantitative multi-driver assessment not only distinguishes where overall compound flooding potential is the highest, but also discriminates which driver combinations are more likely to contribute to compound flooding. We identify that hotspots of compound flooding potential are located along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

This article focuses on hunter-gatherer impact on interglacial vegetation in Europe, using a case study from the Early Holocene (9200–8700 BP). We present a novel agent-based model, hereafter referred to as HUMLAND (HUMan impact on LANDscapes), specifically developed to define key factors in continental-level vegetation changes via assessment of differences between pollen-based reconstruction and dynamic global vegetation model output (climate-based vegetation cover). The identified significant difference between these two datasets can be partially explained by the difference in the models themselves, but also by the fact that climate is not the sole factor responsible for vegetation change. Sensitivity analysis of HUMLAND showed that the intensity of anthropogenic vegetation modification mainly depended on three factors: the number of groups present, their preferences for vegetation openness around campsites, and the size of an area impacted by humans. Overall, both climate and human activities had strong impacts on vegetation openness during the study period. Our modelling results support the hypothesis that European ecosystems were strongly shaped by human activities already in the Mesolithic. • Novel agent-based model designed to explore how diverse factors affected paleo-landscapes. • Study suggests human impact on the environment as the primary non-climate factor affecting landscapes in the Early Holocene. • Modelling results show foragers' impact depends on population size, accessible area and vegetation openness around campsites. [ABSTRACT FROM AUTHOR]

In Oceania, North America and north‐western Europe, after decades of increase, cutaneous malignant melanoma (CMM) rates began to stabilise or decline before 2000. Anecdotal evidence suggests that the reversal of the incidence trend is extending to southern Europe. To obtain a formal confirmation, this nationwide study from Italy investigated the incidence trends by birth cohort. Twenty‐one local cancer registries covering a population of 15 814 455 provided incidence data for primary CMM registered between 1994 and 2013. Trends in age‐standardised rates were analysed using joinpoint regression models and age‐period‐cohort models. Age‐standardised incidence showed a consistent increase throughout the period (estimated annual percent change, 3.6 [95% confidence interval, 3.2‐4.0] among men and 2.5 [2.0‐3.1] among women). This pattern was confirmed by a sensitivity analysis with removal of low‐risk populations of southern Italy. The rates, however, showed a stabilisation or a decrease in men and women aged below 35. Using the cohort of 1949—the median cohort with respect to the number of cases for both genders—as a reference, the incidence rate ratio increased for successive cohorts born until 1973 (women) and 1975 (men), and subsequently tended to decline. For the most recent cohorts in both genders, the risk of disease returned to the level of the cohort of 1949. The changes observed in the latest generations can be interpreted as the earliest manifestations of a birth‐cohort‐dependent incidence decrease. Our study adds to previous data indicating that the reversal of the long‐term upward incidence trend of CMM is extending to southern Europe. What's new? After increasing for many years, malignant melanoma rates began to stabilise or decline in many regions before 2000. Is this also true for southern Europe? In the current study, the authors found that melanoma rates have also began to decline in Italy. The reversal of the long‐term, worldwide increase in melanoma risk seen in other Caucasian populations thus appears to extend to southern Europe. These results indicate that primary prevention strategies have been effective in modifying sun‐exposure habits in this region, and should continue to be reinforced via public health messaging. [ABSTRACT FROM AUTHOR]

State-of-the-art ensemble prediction systems usually provide ensembles with only 20–250 members for estimating the uncertainty of the forecast and its spatial and spatiotemporal covariance. Given that the degrees of freedom of atmospheric models are several magnitudes higher, the estimates are therefore substantially affected by sampling errors. For error covariances, spurious correlations lead to random sampling errors, but also a systematic overestimation of the correlation. A common approach to mitigate the impact of sampling errors for data assimilation is to localize correlations. However, this is a challenging task given that physical correlations in the atmosphere can extend over long distances. Besides data assimilation, sampling errors pose an issue for the investigation of spatiotemporal correlations using ensemble sensitivity analysis. Our study evaluates a statistical approach for correcting sampling errors. The applied sampling error correction is a lookup table–based approach and therefore computationally very efficient. We show that this approach substantially improves both the estimates of spatial correlations for data assimilation as well as spatiotemporal correlations for ensemble sensitivity analysis. The evaluation is performed using the first convective-scale 1000-member ensemble simulation for central Europe. Correlations of the 1000-member ensemble forecast serve as truth to assess the performance of the sampling error correction for smaller subsets of the full ensemble. The sampling error correction strongly reduced both random and systematic errors for all evaluated variables, ensemble sizes, and lead times. [ABSTRACT FROM AUTHOR]

The use of pallets is crucial in supply chain and transportation processes, with wood pallets representing the most common packaging type in the US and in Europe. This work focuses on the environmental and economic impact of wood pallet reverse logistics, quantifying the context in which preemptive remanufacturing schedules are useful. Preemptive schedules allow the service provider to reduce transportation emissions and costs by combining multiple pallet components remanufacturing activities. However, this advantage has to be weighed against the losses associated with repairing or replacing a still functional component earlier than required. An integer linear optimization model analyzes this trade-off, first from an environmental then from an economic perspective. This model is applied using the two most common pallet types as case studies: 48- by 40-inch stringer and block pallets. Different handling and loading scenarios are considered. The impact of transportation distance on the efficiency of preemptive policies is explored through a sensitivity analysis. Results show the positive impact of preemptive remanufacturing on costs and CO 2 -equivalent emissions in all scenarios, with larger benefits in good handling or light loading scenarios. • Preemptive remanufacturing policies for block and stringer pallets are compared. • An optimization model analyzes costs and CO2eq emissions of preemptive repair schedules. • Preemptive policies result in costs and CO2eq emissions reduction by 30–40%. • Up to 50% cost and emission reduction with good handling or light loading conditions. • Results for block pallets are sensitive to distance below 200 km. [ABSTRACT FROM AUTHOR]

Pancreatic adenocarcinoma (PC) is a lethal malignancy that is familial or associated with genetic syndromes in 10% of cases. Gene-based surveillance strategies for at-risk individuals may improve clinical outcomes. However, familial PC (FPC) is plagued by genetic heterogeneity and the genetic basis for the majority of FPC remains elusive, hampering the development of gene-based surveillance programs. The study was powered to identify genes with a cumulative pathogenic variant prevalence of at least 3%, which includes the most prevalent PC susceptibility gene, BRCA2. Since the majority of known PC susceptibility genes are involved in DNA repair, we focused on genes implicated in these pathways. We performed a region-based association study using the Mixed-Effects Score Test, followed by leave-one-out characterization of PC-associated gene regions and variants to identify the genes and variants driving risk associations. We evaluated 398 cases from two case series and 987 controls without a personal history of cancer. The first case series consisted of 109 patients with either FPC (n = 101) or PC at ≤50 years of age (n = 8). The second case series was composed of 289 unselected PC cases. We validated this discovery strategy by identifying known pathogenic BRCA2 variants, and also identified SMG1, encoding a serine/threonine protein kinase, to be significantly associated with PC following correction for multiple testing (p = 3.22x10-7). The SMG1 association was validated in a second independent series of 532 FPC cases and 753 controls (p<0.0062, OR = 1.88, 95%CI 1.17–3.03). We showed segregation of the c.4249A>G SMG1 variant in 3 affected relatives in a FPC kindred, and we found c.103G>A to be a recurrent SMG1 variant associating with PC in both the discovery and validation series. These results suggest that SMG1 is a novel PC susceptibility gene, and we identified specific SMG1 gene variants associated with PC risk. [ABSTRACT FROM AUTHOR]

This study aims to evaluate service quality performance of major LCCs (Low Cost Carriers) in Europe by the MCDM (Multi-Criteria Decision Making) methodology. In addition it focuses on managerial business models and includes the international airline service providers that have applied the cost leadership strategy. In the study passenger reviews based on customer-rating systems are adopted as an alternative data source. For this purpose 24,971 passenger reviews, including 7 evaluation criteria, are analyzed. In this integrated methodology the Entropy method is used to weight the service quality criteria and the WASPAS method is used to rank the airlines. A sensitivity analysis is also applied and the robustness and stability of the application are confirmed. Consequently Jet2.com demonstrates the best service performance overall and legroom is the most important evaluation criterion. [ABSTRACT FROM AUTHOR]

Abstract Background Declining use of bisphosphonates (BP) in the United States and Europe may lead to a widening of the treatment gap for osteoporosis and an increase in fracture rates. However, a shift to non-bisphosphonates and to hospital administered i.v. BPs could lead to overestimation of the treatment gap if analyses are based exclusively on BP prescriptions. When a healthcare system successfully narrows the treatment gap by making appropriate use of anti-osteoporosis drugs, we would expect to see declining rates of osteoporotic fractures with much of the decrease being statistically attributable to medication uptake. We analysed a best-case scenario where all use of BPs, denosumab, raloxifene and PTH analogues - including the oncology area - was contrasted with the trend in hip fracture rates. This scenario also considered users of raloxifene and teriparatide as covered by osteoporosis drugs though the primary RCT for raloxifene showed no risk reduction in nonvertebral fractures and the RCT for teriparatide risk reductions for non-vertebral fractures but not hip fracture specifically. Sensitivity analyses were also done. Methods We used aggregate statistics on hip fracture events and total use of the above medications estimating the number of persons potentially covered. The reduction in hip fracture rates attributable to treatment was estimated using the absolute risk reduction (ARR) found in real-world users of oral alendronate in Denmark with the ARR in the FIT primary prevention arm as an alternative scenario. Results A plateau in use of osteoporosis medications occurred in 2014. Between 2005 and 2015, hip fracture rates declined by 30%. However, only up to 20% of the observed reduction in hip fracture rates was statistically attributable to treatment even in a best-case scenario. Sensitivity analyses where raloxifene and teriparatide were excluded did not impact on this finding. Discussion Anti-osteoporosis treatment in Denmark reached a plateau in 2014 even in a best-case scenario where all dispensations were assumed to be for osteoporosis. Future studies may be able to distinguish between the oncology area and the osteoporosis indication as well as provide a delineation of age and gender demographics among users of hospital administered osteoporosis medications. About 80% of the decline in hip fracture rates appears to be due to factors other than osteoporosis medication. The plateau in use of osteoporosis treatment at a level that is too low to make a meaningful impact on societal fracture burden is problematic given the predicted increased age-specific hip fracture rates. Highlights • Anti-osteoporotic medications in Denmark reached a plateau in 2014, even including hospital administered drugs. • Between 2005 and 2015, hip fracture rates declined by 30% or 3,200 hip fractures. • Medications to prevent hip fractures are underused and account for at most 20% of the reduction in hip fracture rates. • Uptake has plateaued at a level too low to make a meaningful impact on societal fracture burden. • Restricting the analysis to medications with primary RCT evidence for hip fractures did not alter the conclusions. [ABSTRACT FROM AUTHOR]

[Display omitted] • A QMSRA model assesses the spoilage risk of PBMA due to G. stearothermophilus growth. • The effect of climate change on the microbiological stability of PBMA was evaluated. • Current temperatures in South Europe are marginal in controlling its growth in PMBA. • A temperature increase of 2 °C may increase the spoilage risk in whole Europe. • An increase in the heat treatment and insulated transportation may reduce the risk. Geobacillus stearothermophilus is one of the predominant spoilers of UHT-treated food products, due to its extremely heat-resistant spores. However, the surviving spores should be exposed to temperature higher than their minimum growth temperature for a certain time to germinate and grow to spoilage levels. Considering the projected temperature increase due to climate change, the events of non-sterility during distribution and transportation are expected to escalate. Hence, the aim of this study was to build a quantitative microbial spoilage risk assessment (QMRSA) model to quantify the risk of spoilage of plant-based milk alternatives within Europe. The model consists of four main steps: 1. Initial contamination of raw materials 2. Heat inactivation of spores during UHT treatment 3. Partitioning 4. Germination and outgrowth of spores during distribution and storage. The risk of spoilage was defined as the probability of G. stearothermophilus to reach its maximum concentration (N max = 107.5 CFU/mL) at the time of consumption. The assessment was performed for North (Poland) and South (Greece) Europe, and the risk of spoilage was estimated for the current climatic conditions and a climate change scenario. Based on the results, the risk of spoilage was negligible for the North European region, while the risk of spoilage in South Europe was 6.2 × 10−3 95% CI (2.3 × 10−3;1.1 × 10−2) under the current climatic conditions. The risk of spoilage was increased for both tested countries under climate change scenario; from zero to 1.0 × 10−4 in North Europe, risk multiplied 2 or 3 in South Europe depending on air conditioning implementation at consumer's place. Therefore, the heat treatment intensity and the use of insulated trucks during distribution were investigated as mitigation strategies and led to significant reduction of the risk. Overall, the QMRSA model developed in this study can support risk management decisions of these products by quantify the potential risk under current climatic conditions and climate change scenarios. [ABSTRACT FROM AUTHOR]

The improvement of the energy efficiency is one of the strategic goals in Poland as well as in the other European countries. The main aim of this article is to present a method of the assessment of the ecological effects for the investment based on the thermal insulation of the external building walls with the inclusion of the sensitiveness of the chosen variables. The Life Cycle Assessment methodology was used for the assessment of the environmental impact. The increased damage on the environment connected to the production of thermal insulation materials and the decrease of the influence on the environment connected with the decrease of the use of energy in the use phase of the building were taken into consideration. The research also encompasses the variability which is a result of the type of the external building wall, the applied heating source, the type of the thermal insulation material and also the climatic zone in which the building is located. Each examined variant brought positive ecological effects such as the reduction of the environmental load as a result of the thermal insulation of the building. In addition, the sensitivity to different factors that influence the examined ecological effects were also researched. The changes of the environmental load that took place during the production of the heat energy in the building and the changes of the demand for heat energy have the most significant impact on the changes of the ecological effects. [ABSTRACT FROM AUTHOR]

The paper examines determinants of sovereign bond spreads (in relation to Germany) of the peripheral euro area countries in the period 2007Q3-2015Q3. The study indicates that the introduction of the Outright Monetary Transactions (OMTs) by the ECB in the third quarter of 2012 led to a change in the sensitivity of the spreads to the developments of certain macroeconomic fundamentals of these economies. In particular, the ratio of public debt to GDP, which significantly and strongly determined the spreads in the period 2007Q3-2012Q2, proved to be insignificant in the period 2012Q3-2015Q3. In addition, the counterfactual analysis carried out shows that the spreads in the analysed countries would have been much higher if the ECB had not decided to introduce this programme. [ABSTRACT FROM AUTHOR]

Background: Four strategies for very early rule-out of acute myocardial infarction using high-sensitivity cardiac troponin I (hs-cTnI) have been identified. It remains unclear which strategy is most attractive for clinical application.Methods: We prospectively enrolled unselected patients presenting to the emergency department with symptoms suggestive of acute myocardial infarction. The final diagnosis was adjudicated by 2 independent cardiologists. Hs-cTnI levels were measured at presentation and after 1 hour in a blinded fashion. We directly compared all 4 hs-cTnI-based rule-out strategies: limit of detection (LOD, hs-cTnI<2 ng/L), single cutoff (hs-cTnI<5 ng/L), 1-hour algorithm (hs-cTnI<5 ng/L and 1-hour change<2 ng/L), and the 0/1-hour algorithm recommended in the European Society of Cardiology guideline combining LOD and 1-hour algorithm.Results: Among 2828 enrolled patients, acute myocardial infarction was the final diagnosis in 451 (16%) patients. The LOD approach ruled out 453 patients (16%) with a sensitivity of 100% (95% confidence interval [CI], 99.2%-100%), the single cutoff 1516 patients (54%) with a sensitivity of 97.1% (95% CI, 95.1%-98.3%), the 1-hour algorithm 1459 patients (52%) with a sensitivity of 98.4% (95% CI, 96.8%-99.2%), and the 0/1-hour algorithm 1463 patients (52%) with a sensitivity of 98.4% (95% CI, 96.8%-99.2%). Predefined subgroup analysis in early presenters (≤2 hours) revealed significantly lower sensitivity (94.2%, interaction P=0.03) of the single cutoff, but not the other strategies. Two-year survival was 100% with LOD and 98.1% with the other strategies (P<0.01 for LOD versus each of the other strategies).Conclusions: All 4 rule-out strategies balance effectiveness and safety equally well. The single cutoff should not be applied in early presenters, whereas the 3 other strategies seem to perform well in this challenging subgroup.Clinical Trial Registration: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00470587. [ABSTRACT FROM AUTHOR]

Financial data provides a valuable up-to-date knowledge of the world economy. However, it is presented in extremely large data volumes, in diverse formats, and is constantly being updated at a high speed. The Ramex-Forum algorithm is oriented to guide financial experts in finding new and relevant information. We present a sensitivity analysis and new visualizations using an improved version of the Ramex-Forum algorithm. The proposed algorithm is applied to two case studies - the petroleum production chain and the European financial institutions risk analysis. Different combinations of parameters and new ways to visualize data are used. Results highlight the importance of Ramex-Forum for analysing relevant relationships in price variations in financial markets. [ABSTRACT FROM AUTHOR]

Based on a unique composite dataset measuring heterogeneous sports participation, labour market outcomes and local facilities provision, this article examines for the first time the association between different types of sports participation and employment and earnings in England. Clear associations between labour market outcomes and sports participation are established through matching estimation while controlling for some important confounding factors. The results, which are supplemented and supported by a formal sensitivity analysis, suggest a link between different types of sports participation to initial access to employment and then higher income opportunities with ageing. However, these vary between the genders and across sports. Specifically, the results suggest that team sports contribute most to employability, but that this varies by age across genders and that outdoor activities contribute most towards higher incomes. [ABSTRACT FROM AUTHOR]

Background: The new European Society of Cardiology guidelines to rule-in and rule-out acute myocardial infarction (AMI) in the emergency department include a rapid assessment algorithm based on high-sensitivity cardiac troponin and sampling at 0 and 1 hour. Emergency department physicians require high sensitivity to confidently rule-out AMI, whereas cardiologists aim to minimize false-positive results.Methods: High-sensitivity troponin I and T assays were used to measure troponin concentrations in patients presenting with chest-pain symptoms and being investigated for possible acute coronary syndrome at hospitals in New Zealand, Australia, and Canada. AMI outcomes were independently adjudicated by at least 2 physicians. The European Society of Cardiology algorithm performance with each assay was assessed by the sensitivity and proportion with AMI ruled out and the positive predictive value and proportion ruled-in.Results: There were 2222 patients with serial high-sensitivity troponin T and high-sensitivity troponin I measurements. The high-sensitivity troponin T algorithm ruled out 1425 (64.1%) with a sensitivity of 97.1% (95% confidence interval [CI], 94.0%-98.8%) and ruled-in 292 (13.1%) with a positive predictive value of 63.4% (95% CI, 57.5%-68.9%).The high-sensitivity troponin I algorithm ruled out 1205 (54.2%) with a sensitivity of 98.8% (95% CI, 96.4%-99.7%)) and ruled-in 310 (14.0%) with a positive predictive value of 68.1% (95% CI, 62.6%-73.2%).Conclusions: The sensitivity of the European Society of Cardiology rapid assessment 0-/1-hour algorithm to rule-out AMI with high-sensitivity troponin may be insufficient for some emergency department physicians to confidently send patients home. These algorithms may prove useful to identify patients requiring expedited management. However, the positive predictive value was modest for both algorithms. [ABSTRACT FROM AUTHOR]

The country-specific conditions for work and family reconciliation (family policies, labour market structures and gender norms) are believed to influence tensions between paid employment and childbearing. So far there have been very few attempts to quantify these conditions into a single measure which would allow for comparisons across countries of the magnitude of the barriers that working parents encounter. Such a quantitative index could also facilitate a quantitative investigation of the association between the macro-level conditions for work and family reconciliation and fertility at the individual level. In this paper, we seek to fill this gap by proposing a quantitative index of country-specific conditions for work and family reconciliation, which may be used, for example, in a two-level regression framework. The index takes into account all three components of the conditions for work and family reconciliation. We also perform a series of uncertainty and sensitivity analyses which verify the robustness of our assumptions and which illustrate the range of the index volatility. [ABSTRACT FROM AUTHOR]

Tick-borne encephalitis (TBE) is a viral disease endemic in Eurasia. The virus is mainly transmitted to humans via ticks and occasionally via the consumption of unpasteurized milk products. The European Centre for Disease Prevention and Control reported an increase in TBE incidence over the past years in Europe as well as the emergence of the disease in new areas. To better understand this phenomenon, we investigated the drivers of TBE emergence and increase in incidence in humans through an expert knowledge elicitation. We listed 59 possible drivers grouped in eight domains and elicited forty European experts to: (i) allocate a score per driver, (ii) weight this score within each domain, and (iii) weight the different domains and attribute an uncertainty level per domain. An overall weighted score per driver was calculated, and drivers with comparable scores were grouped into three terminal nodes using a regression tree analysis. The drivers with the highest scores were: (i) changes in human behavior/activities; (ii) changes in eating habits or consumer demand; (iii) changes in the landscape; (iv) influence of humidity on the survival and transmission of the pathogen; (v) difficulty to control reservoir(s) and/or vector(s); (vi) influence of temperature on virus survival and transmission; (vii) number of wildlife compartments/groups acting as reservoirs or amplifying hosts; (viii) increase of autochthonous wild mammals; and (ix) number of tick species vectors and their distribution. Our results support researchers in prioritizing studies targeting the most relevant drivers of emergence and increasing TBE incidence.

• There is a growing need for Decision Support Systems in forestry that focus on the understorey. • This paper presents a first prototype of such an understorey Decision Support System. • We developed General Additive Models to predict understorey responses to global change. • Climate warming will shift understorey composition towards more woody species and forest generalists. • Keeping the canopy close can help mitigating this shift by increasing the proportion of forest specialists. • Understorey responses to global change were found to be context-dependent. The temperate forest understorey is rich in terms of vascular plant diversity and plays a vital functional role. Given the sensitivity of this forest layer to forest management and global environmental change and the limited knowledge on its long-term dynamics, there is a need for decision support systems that can guide temperate forest managers to optimize their management in terms of understorey outcomes. In this study, using understorey resurvey data collected from across temperate Europe, we developed Generalized Additive Models (GAM) to predict four understorey properties based on forest management and environmental change data, and implemented this model in a web-based tool as a prototype understorey Decision Support System (DSS). Using seventy-two combined climate change, nitrogen(N) deposition and forest management scenarios, applied to two case study regions in Europe, we predicted temperate forest understorey biodiversity dynamics between 2020 and 2050. A sensitivity analysis subsequently allowed to quantify the relative importance of canopy opening, N deposition and climate change on understorey dynamics. Our study showed that, regardless of regions, understorey richness and the proportion of forest specialists generally decreased among most scenarios, but the proportion of woody species and the understorey vegetation total cover increased. Climate warming, N deposition, and increases in canopy openness all influenced understorey dynamics. Climate warming will shift composition towards a selection of forest generalists and woody species, but a less open canopy could mitigate this shift by increasing the proportion of forest specialists. The case studies also showed that these responses can be context-dependent, especially in terms of responses to N deposition. [ABSTRACT FROM AUTHOR]

We present a study of possible climatic data sets that can be used to perform energy rating calculations on photovoltaic (PV) modules in Europe. We selected five geographic locations across Europe to cover the range of climatic conditions present. In order to assess the validity and significance of such climatic data sets we performed a detailed analysis of the sensitivity of the calculated energy rating to the variability of the input parameters. These are the transmission of the front glass based on the angle of incidence of the irradiance, the spectral response measurement of the PV module, coefficients for calculating module temperature from ambient temperature, and measured power matrices as function of module temperature and irradiance. We found that the calculated energy rating is not sensitive to the first three, but mainly varies due to difference in measured power matrices. This is in particular true for the module performance at low irradiance, and therefore shows a more pronounced difference in climates where such low irradiance conditions occur more frequently, such as in the northern parts of Europe. Nevertheless, the variability found is still less than those between geographic locations. We propose a selection of four energy rating data sets, which differ between them by more than the uncertainty and represent the main climates present across Europe. [ABSTRACT FROM AUTHOR]

Background: Leptospirosis is a neglected zoonosis affecting mainly tropical and subtropical regions worldwide, particularly South America and the Caribbean. As in many other countries, under-reporting of cases was suspected in the French West Indies because of inadequate access to diagnostic tests for the general population. Methodology/Principal findings: In order to estimate the real incidence of leptospirosis in Guadeloupe and Martinique, a study was performed in 2011 using the three prevailing available biological tests for diagnosis: Microscopic Agglutination Test (MAT), IgM ELISA and PCR. The study investigated inpatients and outpatients and used active case ascertainment from data provided by a general practitioners’ sentinel network. The epidemiology of the disease was also described in terms of severity and demographic characteristics. Leptospirosis incidence was estimated at 69.4 (95%CI 47.6–91.1) and 60.6 (95%CI 36.3–85.0) annual cases per 100 000 inhabitants in Guadeloupe and Martinique, respectively, which was 3 and 4 times higher than previous estimations. Conclusion/Significance: Inclusion of PCR and IgM ELISA tests for diagnosis of leptospirosis resulted in improved sensitivity in comparison with MAT alone. Our results highlighted the substantial health burden of the disease in these two territories and the importance of access to appropriate laboratory tests. Based on our results, PCR and IgM ELISA tests have now been included in the list of tests reimbursed by the national system of social security insurance in France. Our results also underline the relevance of implementing an integrated strategy for the surveillance, prevention and control of leptospirosis in the French West Indies. [ABSTRACT FROM AUTHOR]

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models. [ABSTRACT FROM AUTHOR]

Sediment delivery ratios (SDRs) link soil loss to sediment yields (SYs) of river catchments. At large scales, SDR models rely on simple catchment properties. To assess their sensitivity and uncertainty in European regions, I compiled a sediment database and derived 16 soil loss maps varying the approximation of the factors of the universal soil loss equation (USLE). Additionally to parameterizing the USLE, the sensitivity analysis comprised the choice of the soil loss and SDR models. The USLE maps were compared to a Pan-European Soil Erosion Risk Assessment (PESERA) map and two empirical SDR models were applied for explaining the variability of SDR and SY. Most relevant for the model efficiency was the choice of the soil loss model. Unlike the PESERA map, the USLE with the four-parameter SDR model allowed satisfactory results in all regions. Fewer parameters for estimating SDR were less appropriate. Among the USLE factors, the choice of theKfactor was most important. The overall model sensitivity to choosing the USLE map and the SDR model was similar. Based on the sensitivity analysis, a most suitable USLE map for predicting SY of European river catchments is proposed. The uncertainty in USLE estimates resulted in an uncertainty of modelled SY varying from 30% to 60% in different regions. No model realization grasped the variability of SDR and SY, so only regional SDR models were feasible. The model application and evaluation were hampered by unrepresentative sediment data and the inherent limitations of the modelling framework. [ABSTRACT FROM AUTHOR]

ABSTRACT The photovoltaic (PV) market is experiencing vigorous growth, whereas prices are dropping rapidly. This growth has in large part been possible through public support, deserved for its promise to produce electricity at a low cost to the environment. It is therefore important to monitor and minimize environmental impacts associated with PV technologies. In this work, we forecast the environmental performance of crystalline silicon technologies in 2020, the year in which electricity from PV is anticipated to be competitive with wholesale electricity costs all across Europe. Our forecasts are based on technological scenario development and a prospective life cycle assessment with a thorough uncertainty and sensitivity analysis. We estimate that the energy payback time at an in-plane irradiation of 1700 kWh/(m2 year) of crystalline silicon modules can be reduced to below 0.5 years by 2020, which is less than half of the current energy payback time. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: The CAQI or Common Air Quality Index was proposed to facilitate the comparison of air quality in European cities in real-time. There are many air quality indices in use in the world. All are somewhat different in concept and presentation and comparing air quality presentations of cities on the internet was virtually impossible. The CAQI and the accompanying website www.airqualitynow.eu and app were proposed to overcome this problem in Europe. This paper describes the logic of making an index, in particular the CAQI and its update with a grid for PM2.5. To assure a smooth transition to the new calculation scheme we studied the behaviour of the index before and after the changes. We used 2006 Airbase data from 31 urban background and 27 street stations all across Europe (that were monitoring PM2.5 in 2006). The CAQI characterises a city by a roadside and urban background situation. It also insists on a minimum number of pollutants to be included in the calculation. Both were deemed necessary to improve the basis for comparing one city to another. A sensitivity analysis demonstrates the comparative behaviour of the street and urban background stations and presents the sensitivity of the CAQI outcome to the pollutants included in its calculation. [Copyright &y& Elsevier]

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems. [ABSTRACT FROM AUTHOR]

Objective To measure the relative efficiency of primary care (PC) in turning their structures into services delivery and turning their services delivery into quality outcomes. Design Cross-sectional study based on the dataset of the Primary Healthcare Activity Monitor for Europe project. Two Data Envelopment Analysis models were run to compare the relative technical efficiency. A sensitivity analysis of the resulting efficiency scores was performed. Setting PC systems in 22 European countries in 2009/2010. Main Outcome Measures Model 1 included data on PC governance, workforce development and economic conditions as inputs and access, coordination, continuity and comprehensiveness of care as outputs. Model 2 included the previous process dimensions as inputs and quality indicators as outputs. Results There is relatively reasonable efficiency in all countries at delivering as many as possible PC processes at a given level of PC structure. It is particularly important to invest in economic conditions to achieve an efficient structure–process balance. Only five countries have fully efficient PC systems in turning their services delivery into high quality outcomes, using a similar combination of access, continuity and comprehensiveness, although they differ on the adoption of coordination of services. There is a large variation in efficiency levels obtained by countries with inefficient PC in turning their services delivery into quality outcomes. Conclusions Maximizing the individual functions of PC without taking into account the coherence within the health-care system is not sufficient from a policymaker's point of view when aiming to achieve efficiency. [ABSTRACT FROM AUTHOR]

Please cite this paper as: Vega et al. (2012) Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza and Other Respiratory Viruses 7(4), 546-558. Background Timely influenza surveillance is important to monitor influenza epidemics. Objectives (i) To calculate the epidemic threshold for influenza-like illness (ILI) and acute respiratory infections (ARI) in 19 countries, as well as the thresholds for different levels of intensity. (ii) To evaluate the performance of these thresholds. Methods The moving epidemic method (MEM) has been developed to determine the baseline influenza activity and an epidemic threshold. False alerts, detection lags and timeliness of the detection of epidemics were calculated. The performance was evaluated using a cross-validation procedure. Results The overall sensitivity of the MEM threshold was 71·8% and the specificity was 95·5%. The median of the timeliness was 1 week (range: 0-4·5). Conclusions The method produced a robust and specific signal to detect influenza epidemics. The good balance between the sensitivity and specificity of the epidemic threshold to detect seasonal epidemics and avoid false alerts has advantages for public health purposes. This method may serve as standard to define the start of the annual influenza epidemic in countries in Europe. [ABSTRACT FROM AUTHOR]

Abstract: This study derived Species Sensitivity Distributions (SSD), representing a cumulative stressor-response distribution based on single-species sensitivity data, for ozone exposure on natural vegetation. SSDs were constructed for three species groups, i.e. trees, annual grassland and perennial grassland species, using species-specific exposure–response data. The SSDs were applied in two ways. First, critical levels were calculated for each species group and compared to current critical levels for ozone exposure. Second, spatially explicit estimates of the potentially affected fraction of plant species in Northwestern Europe were calculated, based on ambient ozone concentrations. We found that the SSD-based critical levels were lower than for the current critical levels for ozone exposure, with conventional critical levels for ozone relating to 8–20% affected plant species. Our study shows that the SSD concept can be successfully applied to both derive critical ozone levels and estimate the potentially affected species fraction of plant communities along specific ozone gradients. [Copyright &y& Elsevier]

The paper presents the aim and objectives of modernizing the energy system of current buildings as well as of designing and executing new buildings with a high Energy and Environmental Performance. It is necessary to refer to the European Strategy (Europe 2020) and to the European Directives, transposed into the national legislation, while the technical and economic solutions to the objectives resulting from the above mentioned purpose complete the dimension of the logical structure of this procedure for reaching the objectives. The economic and especially social importance of comfortable and hygienic living conditions, without excessive costs and without affecting the climate also stems from the climate impact on the current living conditions and use of energy sources. The summer of 2003 had a tragic aftermath at the European and international level, consisting in over 40000 victims of the heat wave and of the buildings' incapacity to adapt to extremes such as exceptionally intense climate hazards. This highlighted the vulnerability of the built environment compared to climate hazards characterized through an ascending evolution, Romania included. The system of quantitative assessment of the building's Energy and Environmental Performance, part of the procedure for Energy and Environmental Configuration, entails separate expertise and diagnosis phases which allow elaborating scenarios and strategies for energy modernization. The modernization scenarios are elaborated based on the diagnosis of the building, scenarios differentiated through technical and economic indicators. Scenarios allow the modernization strategy to be elaborated. The energy modernization strategy / designing of new, energy performance buildings is based on the Energy Configuration of Buildings which is the detailed modelling of ownership transfer processes and the assessment of economic efficiency of design / exploitation solutions. The calculation methods are subject to validation and sensitivity analysis. The paper presents a case study starting from a condominium in Bucharest, built in 2010. The process was followed starting with the Building's Certification in its current status (falling under the D energy class, mediocre) and ended with the transformation, by means of energy compliance, into a Nearly Zero Energy Building (NZEB). [ABSTRACT FROM AUTHOR]

Life within the soil is vital for maintaining life on Earth due to the numerous ecosystem services that it provides. However, there is evidence that pressures on the soil biota are increasing which may undermine some of these ecosystem services. Current levels of belowground biodiversity are relatively poorly known, and so no benchmark exists by which to measure possible future losses of biodiversity. Furthermore, the relative risk that each type of anthropogenic pressures places on the soil biota remains unclear. Potential threats to soil biodiversity were calculated through the use of a composite score produced from data collected from 20 international experts using the budget allocation methodology. This allowed relative weightings to be given to each of the identified pressures for which data were available in the European Soil Data Centre ( ESDC). A total of seven different indicators were used for calculating the composite scores. These data were applied through a model using Arc GIS to produce a spatial analysis of composite pressures on soil biodiversity at the European scale. The model highlights the variation in the composite result of the potential threats to soil biodiversity. A sensitivity analysis demonstrated that the intensity of land exploitation, both in terms of agriculture and use intensity, as well as in terms of land-use dynamics, were the main factors applying pressure on soil biodiversity. It is important to note that the model should not be viewed as an estimate of the current level of soil biodiversity in Europe, but as an estimate of pressures that are currently being exerted. The results obtained should be seen as a starting point for further investigation on this relatively unknown issue and demonstrate the utility of this type of model which may be applied to other regions and scales. [ABSTRACT FROM AUTHOR]

Species sensitivity distributions (SSDs) developed from individual and population endpoints were compared based on simulations and a case study. The simulations were performed with five invertebrate species accounting for the diversity of benthic macroinvertebrate communities in large European lowland rivers and for five benthic invertebrates used as laboratory species. Population growth rate 10% effective concentration (EC10) values were, in most of the simulations, higher than the lowest of the EC10 values at the individual level. However, for the set of ecologically representative species, the fifth percentile level of this distribution (HC5) was more protective for population endpoints than for individual endpoints. This was the opposite for the set of laboratory species. Population and individual SSDs were also compared based on existing data on Cu for the five laboratory invertebrate species. In this case, the calculated population HC5 value was almost twice the individual value, and the authors showed much reduced variability between species sensitivities at population level compared with individual level. They conclude that population-based HC5 would generally be more protective than individual-based HC5. However, the change of level could reveal higher homogeneity at population level than at individual level, supporting the use of population-based HC5 to avoid overprotection. The authors thus advise the derivation of population-based HC5, as soon as it is possible, to derive such value with a relevant panel of species. Environ. Toxicol. Chem. 2013;32:1173-1177. © 2013 SETAC [ABSTRACT FROM AUTHOR]