Self-efficacy and medicine use for headache among adolescents in Italy: results from the Italian HBSC 2010 study

This article aims first to investigate gender patterns in medicine use, and corresponding headache complaints, in Italian adolescents; second, to examine the association between self-efficacy and medicine use for headache. This study used data from 23,941 15-year-old students participating in the 2009/2010 Health Behaviour in School-aged Children (HBSC) Survey. Self-complete questionnaires devised by the HBSC international group were administered in classrooms. Logistic regression models (controlling demographics: age, gender, and FAS) were used to investigate the association between medicine use for the associated health complaint, and perceived self-efficacy. Overall, prevalence of students reporting medicine use for headache (at least once a month) was 40.1%. Medicine use was significantly more common among girls than among boys for that somatic symptom. The use of medicines was significantly associated with the frequency of the corresponding health complaint. Selfefficacy was associated with a lower use of medicine for headache just for the group with low frequency of headache. In conclusion, self-efficacy may reduce the tendency to use medicines when adolescents report infrequent headaches

Influence of anthropogenic and meteorological drivers on temporal patterns of ammonia emissions from agriculture in the UK

Emissions of trace gases originating from anthropogenic activities are vital input data for chemical transport models (CTMs). Other key input datasets such as meteorological drivers, and biogeochemical and physical processes have been subject to detailed investigation and research in the recent past, while the representation of spatio-temporal aspects of emission data in CTMs has been somewhat neglected. Arguably, this has less impact on the regional to hemispheric or global scale, where the grid sizes of currently applied CTMs represent well mixed average concentrations or deposition values. Evaluating model output against ground-based observations or remote sensing results on these spatial levels may not to be overly sensitive to the temporal (and spatial) profiles of emission input data. With increasing level of detail and spatio-temporal resolution, CTMs applied to determine national or local scale air quality are likely prone to be more sensitive to the spatial and temporal patterns of anthropogenic emissions. The location and timing of emission events - for instance peaks of ammonia emissions following the spring and autumn application of manure and mineral fertilisers - may well determine local concentration or deposition episodes, while not necessarily affecting seasonal or even annual mean values. In the case of agriculture, both anthropogenic activities (e.g. manure spreading and fertilizer application) and meteorological factors (e.g. temperature and seasonality) have been investigated regarding their influence on the spatiotemporal distribution of NH3 emissions (see for instance [1], [2], [4], [5] and [6]). The discussion of results in this case will focus on the impact on the deposition of acidifying and eutrophying substances, as well as the contribution to the formation of ammonium nitrates and sulphates and hence ambient concentrations of secondary particulate matter. This paper discusses results of the application of the EMEP4UK CTM on a 5 km x 5 km resolution for the whole of the United Kingdom. To evaluate the effect of changing the temporal profiles, three different model setups, e.g. using rather coarse and potentially outdated temporal profiles of the EMEP unified model, with varying degrees of detail (in this case, a monthly profile (cf. [3]) vs. 3 hourly emission values[6]) are evaluated against the AGANET measurement network stations across the UK. The discussion of results will focus on (a) the effect of temporal emission profiles on modelled vs. measured concentration/deposition values, (b) the influence on deposition of reactive nitrogen on ecosystems near ammonia sources and (c) the magnitude of influence of anthropogenic activity vs. meteorology for the dispersion of ammonia from agriculture. The results presented in this paper will help to determine the appropriate degree of detail with regard to the temporal profiles of anthropogenic emission data, as collecting detailed statistical data on anthropogenic activities for high spatially resolved model applications can be very time consuming and expensive. In addition, the effect on improving the temporal representation of emissions influenced by both anthropogenic activities and meteorological parameters can contribute to reducing uncertainties in model results that are highly relevant for policy development, e.g. covering aspects of critical load exceedance in vulnerable ecosystems or the exceedance of concentrations of PM

Improving the spatial resolution of air-quality modelling at a European scale – development and evaluation of the Air Quality Re-gridder Model (AQR v1.1)

Currently, atmospheric chemistry and transport models (ACTMs) used to assess impacts of air quality, applied at a European scale, lack the spatial resolution necessary to simulate fine-scale spatial variability. This spatial variability is especially important for assessing the impacts to human health or ecosystems of short-lived pollutants, such as nitrogen dioxide (NO2) or ammonia (NH3). In order to simulate this spatial variability, the Air Quality Re-gridder (AQR) model has been developed to estimate the spatial distributions (at a spatial resolution of 1  ×  1 km2) of annual mean atmospheric concentrations within the grid squares of an ACTM (in this case with a spatial resolution of 50  ×  50 km2). This is done as a post-processing step by combining the coarse-resolution ACTM concentrations with high-spatial-resolution emission data and simple parameterisations of atmospheric dispersion. The AQR model was tested for two European sub-domains (the Netherlands and central Scotland) and evaluated using NO2 and NH3 concentration data from monitoring networks within each domain. A statistical comparison of the performance of the two models shows that AQR gives a substantial improvement on the predictions of the ACTM, reducing both mean model error (from 61 to 41 % for NO2 and from 42 to 27 % for NH3) and increasing the spatial correlation (r) with the measured concentrations (from 0.0 to 0.39 for NO2 and from 0.74 to 0.84 for NH3). This improvement was greatest for monitoring locations close to pollutant sources. Although the model ideally requires high-spatial-resolution emission data, which are not available for the whole of Europe, the use of a Europe-wide emission dataset with a lower spatial resolution also gave an improvement on the ACTM predictions for the two test domains. The AQR model provides an easy-to-use and robust method to estimate sub-grid variability that can potentially be extended to different timescales and pollutants

Body image and psychosocial well-being in early adolescent development.

Introduction: Body dissatisfaction is a determining factor in defining psychosocial well being in early adolescence. During this period, young people progressively redefine their aesthetic standards. This new body concept influences how girls evaluate and accept their own appearance and is related to the psychophysical changes they undergo during this developmental phase. The aim of this study is to investigate how this change in body image evolves in a sample of early adolescent girls. Sample: The sample was composed of 2,408 early adolescent females from the Veneto region, subdivided into three age groups (761 11-year-olds, 734 13-year-olds, and 913 15-year-olds). Results: Correspondence analysis reveals how, in the 11-years-old group, feeling unattractive is only related to being overweight; this relation, however changes with increases age, when feeling unattractive is not anymore a synonymous of being overweight, and a new association can be observed in older girls who feel underweight and perceive themselves as attractive. Conclusion: Body image components change considerably during the early adolescence transition

Stakeholder evaluation of modelled EMEP4UK gridded UK atmospheric composition data

Nine academic and government agency staff where interviewed on their opinion of the EMEP4UK gridded UK atmospheric composition data supplied by Massimo Vieno in connection with WP2.1 of the UK-SCAPE program. The aim of the interviews was to understand from a user’s perspective the utility of the UKSCAPE modelled EMEP4UK gridded UK atmospheric composition data and enable co-production of improvements. Specifically the interviewees opinion of four aspects were determined: • Co-producing impact from this science through Art/Science collaboration • Ease of discovering EMEP4UK gridded UK atmospheric composition data • Data delivery and user co-design improvements, and finally • How the data was used and acknowledged. The interviewees priorities improvements including: • Providing a snippet of R and/or python code to accompany the data • Providing a video of the data showing the spatial and temporal variability of a specific pollutant • Providing a persistent identifier for the data e.g. DOI • Providing an application programming interface enabling connection between computers or between computer programs i.e. API. Snippets of R and python are now under development within the WP2 and implemented in the DataLab (part of the WP2 Data Science Framework) and the other three suggestions will be included in future funding application

Modelling the contribution of SO2 and NOx emissions from international shipping to sulphur and oxidised nitrogen deposition in the United Kingdom

A statistical Lagrangian atmospheric transport model was used to generate annual maps of deposition of sulphur and nitrogen for the United Kingdom at a 5 x 5 km2 resolution for the year 2005 and to assess the contribution attributed to emissions of SO2 and NOx from international shipping. A future emissions scenario for the year 2020 was used to investigate changes in the relative contribution of shipping emissions. The results show that, if shipping emissions are assumed to increase at a rate of 2.5% per year, their relative contribution to total sulphur and oxidised nitrogen deposition are expected to increase from 15% and 12% respectively to 37% and 28% between 2005 and 2020. Enforcement of the International Maritime Organisation (IMO) agreement to reduce the sulphur content in marine fuel to 0.5% was estimated to result in a 30% reduction in total sulphur deposition to the UK for the year 2020 compared to a business as usual scenario, with the result that the relative contribution from shipping to sulphur deposition in the UK would be reduced to 9% of the tota

Global sensitivities of reactive N and S gas and particle concentrations and deposition to precursor emissions reductions

The reduction of fine particles (PM2.5) and reactive N (Nr) and S (Sr) species is a key objective for air pollution control policies because of their major adverse effects on human health, ecosystem diversity, and climate. The sensitivity of global and regional Nr, Sr, and PM2.5 to 20 % and 40 % individual and collective reductions in anthropogenic emissions of NH3, NOx, and SOx (with respect to a 2015 baseline) is investigated using the EMEP MSC-W atmospheric chemistry transport model with WRF meteorology. Regional comparisons reveal that the individual emissions reduction has multiple co-benefits and small disbenefits on different species, and those effects are highly geographically variable. Reductions in NH3 emissions are effective at decreasing NH3 concentrations and deposition but much less so for NH4+. A 40 % NH3 emissions reduction decreases regional average NH3 concentrations by 47&ndash;49 %, while sensitivities of NH4+ concentrations decrease in the order Euro_Medi (Europe and Mediterranean, 18 %), East Asia (15 %), North America (12 %), and South Asia (4 %), reflecting the increasing regional ammonia-richness. A disbenefit is the increased SO2 concentrations in these regions (10&ndash;16 % for 40 % NH3 emissions reductions) because reduced NH3 levels decrease SO2 deposition by altering atmospheric acidity. The 40 % NOx emissions reductions decrease NOx concentrations in East Asia by 45 %, Euro_Medi and North America by ~38 %, and South Asia by 22 %, whilst decreases in fine NO3- are regionally reversed, which is related to enhanced O3 levels in East Asia (and also, but by less, in Euro_Medi), and decreased O3 levels in South Asia (and also, but by less, in North America). Consequently, the oxidation of NOx to NO3- and of SO2 to SO42- is enhanced in East Asia but decreased in South Asia, which in East Asia causes a more effective decrease in NOx and SO2 but a less effective decrease in NO3- and even an increase in SO42-; in South Asia it causes a less effective decrease in NOx and an increase in SO2 but a more effective decrease in NO3- and SO42-. For regional policy making, it is thus important to reduce NH3, NOx and SOx emissions together and/or go for stronger reductions to minimise such adverse effects in East Asia and Euro_Medi. Reductions in SOx emissions are slightly more effective for SO2 than SO42-. A disbenefit is that SOx emissions reductions increase NH3 total deposition and ecosystem eutrophication (~12 % increase for 40 % emissions reduction). PM2.5 mitigation in South Asia is most sensitive to 40 % SOx reduction (3.10 &mu;g m-3, 10 %) and least sensitive to NH3 reduction (0.29 &mu;g m-3, 1 %), which is because South Asia is so ammonia-rich that reducing NH3 has little impact. The most effective measure for North America is reducing NOx emissions with an 8 % (0.63 &mu;g m-3) decrease in PM2.5 in response to a 40 % reduction. In Euro_Medi, the sensitivities of PM2.5 to 40 % individual emissions reductions range 5&ndash;8 % (0.55&ndash;0.82 &mu;g m-3). In the UK and Scandinavia PM2.5 is more sensitive to NH3, in central Europe it is more sensitive to NOx, while in the Mediterranean it is more sensitive to SOx. In East Asia, reductions in SOx, NOx and NH3 emissions are almost equally effective with PM2.5 sensitivities to 40 % reductions of 7&ndash;8 % (1.89&ndash;2.33 &mu;g m-3). Due to the varying contributions of SIA, PM2.5 sensitivities to 40 % collective reductions in all 3 precursors decrease in the order East Asia (20 %), Euro_Medi and North America (17 %), South Asia (13 %). The geographically-varying non-linear chemical responses of Nr, Sr, and PM2.5 to emissions reductions revealed by this work show the importance of both prioritising emissions strategies in different regions and combining several precursor reductions together to maximise the policy effectiveness.</p

Air quality simulations for London using a coupled regional-to-local modelling system

A coupled regional-to-local modelling system comprising a regional chemistry–climate model with 5km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2.5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30% for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2.5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13% of the area of London exceeded the EU limit value of 40µgm−3 for annual average NO2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25µgm−3 for PM10 and PM2.5 respectively were negligible

Advanced methods for uncertainty assessment and global sensitivity analysis of a Eulerian atmospheric chemistry transport model

Atmospheric chemistry transport models (ACTMs) are extensively used to provide scientific support for the development of policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Therefore, it is essential to quantitatively assess the level of model uncertainty and to identify the model input parameters that contribute the most to the uncertainty. For complex process-based models, such as ACTMs, uncertainty and global sensitivity analyses are still challenging and are often limited by computational constraints due to the requirement of a large number of model runs. In this work, we demonstrate an emulator-based approach to uncertainty quantification and variance-based sensitivity analysis for the EMEP4UK model (regional application of the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre-West). A separate Gaussian process emulator was used to estimate model predictions at unsampled points in the space of the uncertain model inputs for every modelled grid cell. The training points for the emulator were chosen using an optimised Latin hypercube sampling design. The uncertainties in surface concentrations of O3, NO2, and PM2.5 were propagated from the uncertainties in the anthropogenic emissions of NOx, SO2, NH3, VOC, and primary PM2.5 reported by the UK National Atmospheric Emissions Inventory. The results of the EMEP4UK uncertainty analysis for the annually averaged model predictions indicate that modelled surface concentrations of O3, NO2, and PM2.5 have the highest level of uncertainty in the grid cells comprising urban areas (up to ±7 %, ±9 %, and ±9 %, respectively). The uncertainty in the surface concentrations of O3 and NO2 were dominated by uncertainties in NOx emissions combined from non-dominant sectors (i.e. all sectors excluding energy production and road transport) and shipping emissions. Additionally, uncertainty in O3 was driven by uncertainty in VOC emissions combined from sectors excluding solvent use. Uncertainties in the modelled PM2.5 concentrations were mainly driven by uncertainties in primary PM2.5 emissions and NH3 emissions from the agricultural sector. Uncertainty and sensitivity analyses were also performed for five selected grid cells for monthly averaged model predictions to illustrate the seasonal change in the magnitude of uncertainty and change in the contribution of different model inputs to the overall uncertainty. Our study demonstrates the viability of a Gaussian process emulator-based approach for uncertainty and global sensitivity analyses, which can be applied to other ACTMs. Conducting these analyses helps to increase the confidence in model predictions. Additionally, the emulators created for these analyses can be used to predict the ACTM response for any other combination of perturbed input emissions within the ranges set for the original Latin hypercube sampling design without the need to rerun the ACTM, thus allowing for fast exploratory assessments at significantly reduced computational costs