EURODELTA-Trends, a multi-model experiment of air quality hindcast in Europe over 1990–2010
Journal article, 2017

The 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.

Author

Augustin Colette

Institut National de l'Environnement Industriel et des Risques (INERIS)

Camilla Andersson

SMHI

Astrid Manders

Netherlands Organisation for Applied Scientific Research (TNO)

Kathleen Mar

Institute for Advanced Sustainability Studies (IASS)

Mihaela Mircea

ENEA Centro Ricerche Bologna

Maria-Teresa Pay

Barcelona Supercomputing Center (BSC)

Valentin Raffort

École des Ponts ParisTech

S. Tsyro

Norwegian Meteorological Institute

C. Cuvelier

EU Joint Research Centre (JRC)

Mario Adani

ENEA Centro Ricerche Bologna

B. Bessagnet

Institut National de l'Environnement Industriel et des Risques (INERIS)

Robert Bergström

SMHI

Microwave and Optical Remote Sensing

Gino Briganti

ENEA Centro Ricerche Bologna

Tim Butler

Institute for Advanced Sustainability Studies (IASS)

Andrea Cappelletti

ENEA Centro Ricerche Bologna

Florian Couvidat

Institut National de l'Environnement Industriel et des Risques (INERIS)

Massimo D'Isidoro

ENEA Centro Ricerche Bologna

Thierno Doumbia

Pantheon-Sorbonne University Paris

Hilde Fagerli

Norwegian Meteorological Institute

C. Granier

Pantheon-Sorbonne University Paris

University of Colorado at Boulder

C. Heyes

International Institute for Applied Systems Analysis (IIASA -Austria)

Z. Klimont

International Institute for Applied Systems Analysis (IIASA -Austria)

Narendra Ojha

Max Planck Institute for Chemistry

Noelia Otero

Institute for Advanced Sustainability Studies (IASS)

M. Schaap

Netherlands Organisation for Applied Scientific Research (TNO)

Katarina Sindelarova

Pantheon-Sorbonne University Paris

Annemiek I. Stegehuis

The French Alternative Energies and Atomic Energy Commission (CEA)

Yelva Roustan

École des Ponts ParisTech

R. Vautard

The French Alternative Energies and Atomic Energy Commission (CEA)

Erik van Meijgaard

Royal Netherlands Meteorological Institute

Marta G. Vivanco

Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (Ciemat)

Peter Wind

Universitetet i Tromsö

Geoscientific Model Development

1991-959X (ISSN)

Vol. 10 9 3255-3276

Subject Categories

Meteorology and Atmospheric Sciences

Roots

Basic sciences

DOI

10.5194/gmd-10-3255-2017

More information

Latest update

4/22/2020