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AbstractVolcanic eruptions take place in Iceland about once every 3 to 5 years. Ash emissions from these eruptions can cause significant disruption to air traffic over Europe and the North Atlantic as is evident from the 2010 eruption of Eyjafjallajökull. Sulfur dioxide (SO2) is also emitted by volcanoes, but there are no criteria to define when airspace is considered hazardous or nonhazardous. However, SO2 is a well‐known ground‐level pollutant that can have detrimental effects on human health. We have used the United Kingdom Met Office's NAME (Numerical Atmospheric‐dispersion Modelling Environment) model to simulate SO2 mass concentrations that could occur in European and North Atlantic airspace for a range of hypothetical explosive eruptions in Iceland with a probability to occur about once every 3 to 5 years. Model performance was evaluated for the 2010 Eyjafjallajökull summit eruption against SO2 vertical column density retrievals from the Ozone Monitoring Instrument and in situ measurements from the United Kingdom Facility for Airborne Atmospheric Measurements research aircraft. We show that at no time during the 2010 Eyjafjallajökull eruption did SO2 mass concentrations at flight altitudes violate European air quality standards. In contrast, during a hypothetical short‐duration explosive eruption similar to Hekla in 2000 (emitting 0.2 Tg of SO2 within 2 h, or an average SO2 release rate 250 times that of Eyjafjallajökull 2010), simulated SO2 concentrations are greater than 1063 µg/m3 for about 48 h in a small area of European and North Atlantic airspace. By calculating the occurrence of aircraft encounters with the volcanic plume of a short‐duration eruption, we show that a 15 min or longer exposure of aircraft and passengers to concentrations ≥500 µg/m3 has a probability of about 0.1%. Although exposure of humans to such concentrations may lead to irritations to the eyes, nose and, throat and cause increased airway resistance even in healthy individuals, the risk is very low. However, the fact that volcanic ash and sulfur species are not always collocated and that passenger comfort could be compromised might be incentives to provide real‐time information on the presence or absence of volcanic SO2. Such information could aid aviation risk management during and after volcanic eruptions.

Description of the R program for computing the homogeneity test Q Îł .

AbstractThis study analyses point forecasts of exact scoreline outcomes for football matches in the English Premier League. These forecasts were made for distinct competitions and originally judged differently. We compare these with implied probability forecasts using bookmaker odds and a crowd of tipsters, as well as point and probability forecasts generated from a statistical model. From evaluating these sources and types of forecast, using various methods, we argue that regression encompassing is the most appropriate way to compare point and probability forecasts, and find that both these types of forecasts for football match scorelines generally add information to one another.

The stable carbon isotope composition of dissolved inorganic carbon (δ13CDIC) in seawater was measured in a batch process for 552 samples collected during two cruises in the northeastern Atlantic and Nordic Seas from June to August 2012. One cruise was part of the UK Ocean Acidification research programme, and the other was a repeat hydrographic transect of the Extended Ellett Line. In combination with measurements made of other variables on these and other cruises, these data can be used to constrain the anthropogenic component of dissolved inorganic carbon (DIC) in the interior ocean, and to help to determine the influence of biological carbon uptake on surface ocean carbonate chemistry. The measurements have been processed, quality-controlled and submitted to an in-preparation global compilation of seawater δ13CDIC data, and are available from the British Oceanographic Data Centre. The observed δ13CDIC values fall in a range from −0.58 to +2.37 ‰, relative to the Vienna Pee Dee Belemnite standard. The mean of the absolute differences between samples collected in duplicate in the same container type during both cruises and measured consecutively is 0.10 ‰, which corresponds to a 1σ uncertainty of 0.09 ‰, and which is within the range reported by other published studies of this kind. A crossover analysis was performed with nearby historical δ13CDIC data, indicating that any systematic offsets between our measurements and previously published results are negligible. Data doi:10.5285/09760a3a-c2b5-250b-e053-6c86abc037c0 (northeastern Atlantic), doi:10.5285/09511dd0-51db-0e21-e053-6c86abc09b95 (Nordic Seas).

International audience; Several studies have reported a decline in incidence of dementia which may have large implications for the projected burden of disease, and provide important guidance to preventive efforts. However, reports are conflicting or inconclusive with regard to the impact of gender and education with underlying causes of a presumed declining trend remaining largely unidentified. The Alzheimer Cohorts Consortium aggregates data from nine international population-based cohorts to determine changes in the incidence of dementia since 1990. We will employ Poisson regression models to calculate incidence rates in each cohort and Cox proportional hazard regression to compare 5-year cumulative hazards across study-specific epochs. Finally, we will meta-analyse changes per decade across cohorts, and repeat all analysis stratified by sex, education and APOE genotype. In all cohorts combined, there are data on almost 69,000 people at risk of dementia with the range of follow-up years between 2 and 27. The average age at baseline is similar across cohorts ranging between 72 and 77. Uniting a wide range of disease-specific and methodological expertise in research teams, the first analyses within the Alzheimer Cohorts Consortium are underway to tackle outstanding challenges in the assessment of time-trends in dementia occurrence.

Interannual variability in the global land carbon sink is strongly related to variations in tropical temperature and rainfall. This association suggests an important role for moisture-driven fluctuations in tropical vegetation productivity, but empirical evidence to quantify the responsible ecological processes is missing. Such evidence can be obtained from tree-ring data that quantify variability in a major vegetation productivity component: woody biomass growth. Here we compile a pantropical tree-ring network to show that annual woody biomass growth increases primarily with dry-season precipitation and decreases with dry-season maximum temperature. The strength of these dry-season climate responses varies among sites, as reflected in four robust and distinct climate response groups of tropical tree growth derived from clustering. Using cluster and regression analyses, we find that dry-season climate responses are amplified in regions that are drier, hotter and more climatically variable. These amplification patterns suggest that projected global warming will probably aggravate drought-induced declines in annual tropical vegetation productivity. Our study reveals a previously underappreciated role of dry-season climate variability in driving the dynamics of tropical vegetation productivity and consequently in influencing the land carbon sink.