Mapping the distribution of Well-Being in Europe beyond national borders

Well-being is a concept difficult to define and eventually harder to quantify. The idea of providing descriptions and metrics to evaluate well-being goes back to Aristotle (1095 bc) and from there an increasingly large number of studies attempted to quantify well-being of individuals and societies. Well-being is generally perceived as a description of the state of human life which always captured the attention of sociologists, economists, psychologist, politicians and citizens, making it a largely debated interdisciplinary topic. In particular in recent times, characterized by even increasing concerns related to the economic and the environmental situation, an increasing attention has been devoted to determining integrated descriptions to include all the aspects of human life. In addition, a large attention, demonstrated by the increasing literature on the topic, has also been devoted to the contribution of politics and societal organization in the progress toward well-being. The first part of this report tries to review the existing literature on well-being. Two main broad wellbeing approaches will be considered, the subjective and the objective approaches. For every one of them, the main definitions, the most important theoretical perspectives and the most relevant metrics and quantifications will be reported. The major contribution is to provide a synthesis of the vast literature that exists on the concept of well-being. In addition, by presenting the most recent well-being approach based on the integration between the objective and the subjective ones, an overview of the future directions of well-being investigations is also provided.JRC.H.2-Air and Climat

Advancing Approaches to the Evaluation of Regional Scale Photochemical Air Quality Modeling Systems

Report on the first AQMEII workshop held in Stresa in May 2009JRC.DDG.H.4-Transport and air qualit

On Application of the "Hot-run" Version of the ENSEMBLE System to the ECURIE Level 3 Exercise

The ENSEMBLE system has been created with the primary aim of harmonizing the information coming from the various countries and to work out a reconciled European long range atmospheric dispersion ensemble forecast. The concept of multi-model ensemble dispersion forecast consists of the qualitative and quantitative analysis of the results produced by several modeling tools on the same case, to produce a composite picture that includes all contributions from the various simulations. This analysis has the advantage of taking into account all possible forecasted scenarios and to determine the level of consensus among the various modeling tools. Within ENSEMBLE the differences in atmospheric dispersion prediction become and asset as they are used to determine the forecast reliability.JRC.H.4-Transport and air qualit

Seeking for the Rational Basis of the Median Model: The Optimal Combination of Multi-model ENSEMBLE Results

In this paper we present an approach for the statistical analysis of multi-model ENSEMBLE results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release 5 of radioactive nuclides. We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach called ‘median model’, originally introduced in Galmarini et al., 2004 a,b. This approach also provides a way to systematically reduce (and quantify) model uncertainties, thus supporting the decision-making process and/or regulatory-purpose activities in a very effective manner.JRC.H.4-Transport and air qualit

Numerical weather Simulations in Support to the CCU CAML Lidar Measurements: Preliminary Results for the Case Study of 21st September 2006

The report describes a series of weather numerical mesoscale simulations performed in high resolution to understand to which extent the lidar-detected evolution of the particles distribution along the vertical could be explained by the boundary layer and/or horizontal transport processes. A particular stress was put on investigation of boundary layer parameters. The case study of 21st September was chosen for simulations, when the CCU-CAML lidar at Ispra registered quite high values of aerosols up to 1 km altitude, and the lidar revealed a descent of the highest aerosol loads towards the ground during the morning.JRC.H.4-Transport and air qualit

Support to the review of the Thematic Strategy on Air Pollution: JRC’s contribution to the 2nd Stakeholder meeting January 2012

Although efforts of the EU to reduce air pollution have led to important reductions of emissions within the Member States, millions of people are still exposed to air pollutants at concentration levels that may endanger their health and air pollution is still causing relevant damage to crops and ecosystems. On this background, the European Commission has decided to review its Thematic Strategy for Air Pollution (TSAP) by 2013 at latest, and do this through a consultation process, led by DG ENV, with a broad group of stakeholders. The present report contains the presentations made by JRC staff at the second Stakeholder Meeting, held in January 2012JRC.H.2-Air and Climat

Trace gas/aerosol boundary concentrations and their impacts on continental-scale AQMEII modeling domains

Copyright 2011 Elsevier B.V., All rights reserved.Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 "cut-outs" from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care.Peer reviewedFinal Accepted Versio

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt