BUILDING BRIDGES FOR INNOVATION IN AGEING : SYNERGIES BETWEEN ACTION GROUPS OF THE EIP ON AHA

The Strategic Implementation Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) proposed six Action Groups. After almost three years of activity, many achievements have been obtained through commitments or collaborative work of the Action Groups. However, they have often worked in silos and, consequently, synergies between Action Groups have been proposed to strengthen the triple win of the EIP on AHA. The paper presents the methodology and current status of the Task Force on EIP on AHA synergies. Synergies are in line with the Action Groups' new Renovated Action Plan (2016-2018) to ensure that their future objectives are coherent and fully connected. The outcomes and impact of synergies are using the Monitoring and Assessment Framework for the EIP on AHA (MAFEIP). Eight proposals for synergies have been approved by the Task Force: Five cross-cutting synergies which can be used for all current and future synergies as they consider overarching domains (appropriate polypharmacy, citizen empowerment, teaching and coaching on AHA, deployment of synergies to EU regions, Responsible Research and Innovation), and three cross-cutting synergies focussing on current Action Group activities (falls, frailty, integrated care and chronic respiratory diseases).Peer reviewe

PM trends in Europe : multi-model and monitoring assessment

PM trends in Europe during the last decades have been assessed using a multi-model approach in the framework of Eurodelta-TRENDS exercise initiated by the European Monitoring and Evaluation Program Task Force on Measurements and Modeling (EMEP-TFMM). Seven regional models (EMEP/MSC-W, CHIMERE, CMAQ, LOTOS-EUROS, MINNI, Polair3D and WRF-Chem, participated in the EURODELTA-Trends exercise, which builds upon previous iterations of the CITYDELTA and EURODELTA projects (Thunis et al., 2007; Cuvelier et al., 2007; Bessagnet et al., 2014). Three of the models performed a 21-year hindcast over Europe for the 1990-2010 period, while all the models made calculations for the years 1990, 2000 and 2010. In addition, a series of sensitivity tests have been performed with the purpose of studying the role of meteorological variability, emission changes and boundary conditions. For the period of 2001-2010, for which enough of PM monitoring data is available, the trends in PM10 and PM2.5 have been studied based on both modelling results and measurement data. The Mann-Kendall test are applied to calculated and measured annual mean concentrations to detect significant (90% probability) trends, whereas the Sen’s slopes are calculated to estimate the absolute and relative declines in PM..

Twenty years of ozone air quality in Europe: trends in models and measurements

The EURODELTA-Trends exercise is a multi-model experiment in which seven regional models performed an air quality hindcast over Europe for the 1990-2010 period at regional-scale resolution (25km). This twenty-year lookback was designed to complement an investigation of observed European air quality trends over the same time period, undertaken by the European Monitoring and Evaluation Program Task Force on Measurements and Modeling (EMEP-TFMM). Observations at rural ground-based monitoring stations indicate that peak episodic ozone, represented by, e.g., 98th percentile of maximum daily 8-hour average ozone (MDA8), have decreased in Europe over the 1990-2010 period. Annual average ozone, on the other hand, was increasing during the 1990-2000 period, but showed a decreasing trend over the 2000-2010 period. Here, the first results of the Eurodelta-Trends exercise for ozone will be presented, with a focus on (1) the capability of the participating models to reproduce the observed trends in European ozone between 1990 and 2010 and (2) the assessment of trends causes, such as changes in precursor emissions and/or meteorology. Seven regional models, including six regional Chemistry-Transport Models (EMEP-MSCW, Chimere, CMAQ, LOTOS-EUROS, MINNI, and Polyphemus) and the online coupled model WRF-Chem, participated in the EURODELTA-Trends exercise, which builds upon previous iterations of the CITYDELTA and EURODELTA projects (Thunis et al., 2007; Bessagnet et al., 2014; Cuvelier et al., 2007). Model simulations for EURODELTATrends included a number of time-slice sensitivity experiments for the years 1990, 2000, and 2010, designed to isolate the contribution of European emission changes, boundary conditions (i.e. extra-European influence), and meteorology on surface ozone concentrations. Four of the participating models performed a full 21-year hindcast for 1990-2010. A second 21-year simulation was performed using 2010 emissions for the whole time period, in order to investigate the role of meteorological variability in the modeled trends. Based on these model results, our understanding of tropospheric ozone drivers in Europe will be discussed

An evaluation of European nitrogen and sulfur wet deposition and their trends estimated by six chemistry transport models for the period 1990-2010

The wet deposition of nitrogen and sulfur in Europe for the period 1990–2010 was estimated by six atmospheric chemistry transport models (CHIMERE, CMAQ, EMEP MSC-W, LOTOS-EUROS, MATCH and MINNI) within the framework of the EURODELTA-Trends model intercomparison. The simulated wet deposition and its trends for two 11-year periods (1990–2000 and 2000–2010) were evaluated using data from observations from the EMEP European monitoring network. For annual wet deposition of oxidised nitrogen (WNOx), model bias was within 30 % of the average of the observations for most models. There was a tendency for most models to underestimate annual wet deposition of reduced nitrogen (WNHx), although the model bias was within 40 % of the average of the observations. Model bias for WNHx was inversely correlated with model bias for atmospheric concentrations of NH3+NH+4 , suggesting that an underestimation of wet deposition partially contributed to an overestimation of atmospheric concentrations. Model bias was also within about 40 % of the average of the observations for the annual wet deposition of sulfur (WSOx) for most models. Decreasing trends in WNOx were observed at most sites for both 11-year periods, with larger trends, on average, for the second period. The models also estimated predominantly decreasing trends at the monitoring sites and all but one of the models estimated larger trends, on average, for the second period. Decreasing trends were also observed at most sites for WNHx, although larger trends, on average, were observed for the first period. This pattern was not reproduced by the models, which estimated smaller decreasing trends, on average, than those observed or even small increasing trends. The largest observed trends were for WSOx, with decreasing trends at more than 80 % of the sites. On average, the observed trends were larger for the first period. All models were able to reproduce this pattern, although some models underestimated the trends (by up to a factor of 4) and others overestimated them (by up to 40 %), on average. These biases in modelled trends were directly related to the tendency of the models to under- or overestimate annual wet deposition and were smaller for the relative trends (expressed as % yr−1 relative to the deposition at the start of the period). The fact that model biases were fairly constant throughout the time series makes it possible to improve the predictions of wet deposition for future scenarios by adjusting the model estimates using a bias correction calculated from past observations. An analysis of the contributions of various factors to the modelled trends suggests that the predominantly decreasing trends in wet deposition are mostly due to reductions in emissions of the precursors NOx, NH3 and SOx. However, changes in meteorology (e.g. precipitation) and other (non-linear) interactions partially offset the decreasing trends due to emission reductions during the first period but not the second. This suggests that the emission reduction measures had a relatively larger effect on wet deposition during the second period, at least for the sites with observations.publishedVersio

EURODELTA-Trends, a multi-model experiment of air quality hindcast in Europe over 1990–2010

International audienceThe EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTA-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions, and (iii) meteorology complements it. The most demanding tier consists of two complete time series from 1990 to 2010, simulated using either time-varying emissions for corresponding years or constant emissions.Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing

Introduction

International audienc