A
Alberto Maurizi
Researcher at National Research Council
Publications - 63
Citations - 1476
Alberto Maurizi is an academic researcher from National Research Council. The author has contributed to research in topics: Air quality index & Turbulence. The author has an hindex of 19, co-authored 62 publications receiving 1344 citations. Previous affiliations of Alberto Maurizi include Faculdade de Engenharia da Universidade do Porto.
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Journal ArticleDOI
Online coupled regional meteorology chemistry models in Europe: current status and prospects
Alexander Baklanov,Katharina Heinke Schlünzen,Peter Suppan,José María Baldasano,Dominik Brunner,Sebnem Aksoyoglu,Greg Carmichael,John Douros,Johannes Flemming,Renate Forkel,Stefano Galmarini,Michael Gauss,Georg Grell,Marcus Hirtl,Sylvain M. Joffre,Oriol Jorba,Eigil Kaas,Marko Kaasik,George Kallos,X. Kong,Ulrik Smith Korsholm,A. Kurganskiy,Jonilda Kushta,Ulrike Lohmann,Alexander Mahura,Astrid Manders-Groot,Alberto Maurizi,Nicolas Moussiopoulos,S. T. Rao,Nicholas Savage,Christian Seigneur,Ranjeet S. Sokhi,Efisio Solazzo,Stavros Solomos,B. S. Sørensen,George Tsegas,Elisabetta Vignati,Bernhard Vogel,Yang Zhang +38 more
TL;DR: A comprehensive review of the current research status of online coupled meteorology and atmospheric chemistry modelling within Europe and highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities.
Journal ArticleDOI
Air quality trends in Europe over the past decade: a first multi-model assessment
Augustin Colette,Claire Granier,Øivind Hodnebrog,Hermann Jakobs,Alberto Maurizi,Agnes Nyiri,Bertrand Bessagnet,Ariela D'Angiola,Massimo D'Isidoro,Michael Gauss,F. Meleux,Michael Memmesheimer,Aude Mieville,Laurence Rouil,Felicita Russo,Sverre Solberg,Frode Stordal,Francesco Tampieri +17 more
TL;DR: In this article, the authors discuss the capability of current state-of-the-art chemistry and transport models to reproduce air quality trends and inter-annual variability and conclude that emission management strategies have had a significant impact over the past 10 yr, hence supporting further emission reductions strategies.
Journal ArticleDOI
Comparison of OMI NO2 tropospheric columns with an ensemble of global and European regional air quality models
Vincent Huijnen,Henk Eskes,Anastasia Poupkou,Hendrik Elbern,K. F. Boersma,Gilles Foret,Mikhail Sofiev,Alvaro Valdebenito,Johannes Flemming,O. Stein,A. Gross,Lennart Robertson,Massimo D'Isidoro,Ioannis Kioutsioukis,E. Friese,Bjarne Amstrup,Robert Bergström,Achim Strunk,Julius Vira,Denis Zyryanov,Denis Zyryanov,Alberto Maurizi,Dimitrios Melas,V.-H. Peuch,Christos Zerefos +24 more
TL;DR: In this article, a comparison of tropospheric NO2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008-June 2009 over Europe, is presented.
Air quality trends in Europe over the past decade: a first multimodel assessment
Augustin Colette,Bertrand Bessagnet,Ariela D'Angiola,Michael Gauss,Claire Granier,Øivind Hodnebrog,Hermann Jakobs,Alberto Maurizi,F. Meleux,M. Memmesheimer,Agnes Nyiri,Laurence Rouil,Felicita Russo,Sverre Solberg,Frode Stordal,Francesco Tampieri +15 more
TL;DR: In this paper, the capability of current state-of-the-art chemistry and transport models to reproduce air quality trends and inter-annual variability in order to better understand their strength and weaknesses before such tools are implemented for future air quality projections is discussed.
Journal ArticleDOI
A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals
Ioannis Binietoglou,Sara Basart,Lucas Alados-Arboledas,Vassilis Amiridis,Athina Argyrouli,Holger Baars,José María Baldasano,Dimitris Balis,Livio Belegante,Juan Antonio Bravo-Aranda,Pasquale Burlizzi,Víctor M. S. Carrasco,Anatoli Chaikovsky,Adolfo Comerón,Giuseppe D'Amico,Maria Filioglou,María José Granados-Muñoz,Juan Luis Guerrero-Rascado,Luka Ilić,Panagiotis Kokkalis,Alberto Maurizi,Lucia Mona,F. Monti,Constantino Muñoz-Porcar,Doina Nicolae,Alexandros Papayannis,Gelsomina Pappalardo,Goran Pejanovic,Sergio Pereira,Maria Rita Perrone,Aleksander Pietruczuk,Michał Posyniak,Francesc Rocadenbosch,Alejandro Rodríguez-Gómez,Michaël Sicard,Nikolaos Siomos,Artur Szkop,Enric Terradellas,Alexandra Tsekeri,Ana Vukovic,Ulla Wandinger,J. Wagner +41 more
Abstract: . Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.