Atmospheric composition forecasting in Europe

The atmospheric composition is a societal issue and, following new European directives, its forecast is now recommended to quantify the air quality. It concerns both gaseous and particles species, identified as potential problems for health. In Europe, numerical systems providing daily air quality forecasts are numerous and, mostly, operated by universities. Following recent European research projects (GEMS, PROMOTE), an organization of the air quality forecast is currently under development. But for the moment, many platforms exist, each of them with strengths and weaknesses. This overview paper presents all existing systems in Europe and try to identify the main remaining gaps in the air quality forecast knowledge. As modeling systems are now able to reasonably forecast gaseous species, and in a lesser extent aerosols, the future directions would concern the use of these systems with ensemble approaches and satellite data assimilation. If numerous improvements were recently done on emissions and chemistry knowledge, improvements are still needed especially concerning meteorology, which remains a weak point of forecast systems. Future directions will also concern the use of these forecast tools to better understand and quantify the air pollution impact on health.

[1]  Walter F. Dabberdt,et al.  Uncertainty, ensembles and air quality dispersion modeling: applications and challenges , 2000 .

[2]  Rohit Mathur,et al.  Assessment of an ensemble of seven real-time ozone forecasts over eastern North America during the summer of 2004 , 2005 .

[3]  Joakim Langner,et al.  An Eulerian limited-area atmospheric transport model , 1999 .

[4]  B. Fay,et al.  Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia , 2006 .

[5]  M. Kolehmainen,et al.  Neural networks and periodic components used in air quality forecasting , 2001 .

[6]  Gabriel Ibarra-Berastegi,et al.  From diagnosis to prognosis for forecasting air pollution using neural networks: Air pollution monitoring in Bilbao , 2008, Environ. Model. Softw..

[7]  Xavier Querol,et al.  Caliope: an operational air quality forecasting system for the Iberian Peninsula, Balearic Islands and Canary Islands – first annual evaluation and ongoing developments , 2008 .

[8]  J. Bartzis,et al.  Data assimilation in meteorological pre-processors: Effects on atmospheric dispersion simulations , 2007 .

[9]  G. Kallos,et al.  Forecast errors in dust vertical distributions over Rome (Italy): Multiple particle size representation and cloud contributions , 2007 .

[10]  F. Meleux,et al.  Predictability of European air quality: Assessment of 3 years of operational forecasts and analyses by the PREV'AIR system , 2008 .

[11]  Ana Isabel Miranda,et al.  Air pollution forecast in Portugal: a demand from the new air quality framework directive , 2005 .

[12]  Transboundary particulate matter in Europe; EMEP Status Report 4/2010 , 2010 .

[13]  Gavin C. Cawley,et al.  Statistical models to assess the health effects and to forecast ground-level ozone , 2006, Environ. Model. Softw..

[14]  J. Goldammer,et al.  Modeling of carbonaceous particles emitted by boreal and temperate wildfires at northern latitudes , 2000 .

[15]  Nelson L. Seaman,et al.  Meteorological modeling for air-quality assessments , 2000 .

[16]  Hendrik Feldmann,et al.  NUMERICAL FORECAST OF AIR POLLUTION - ADVANCES AND PROBLEMS , 2005 .

[17]  V. Peuch,et al.  Surface Exchanges in the Multiscale Chemistry and Transport Model MOCAGE , 2002 .

[18]  Wei-Kuo Tao,et al.  Multiscale cloud system modeling , 2009 .

[19]  Bertrand Bessagnet,et al.  Modeling dust emissions and transport within Europe: The Ukraine March 2007 event , 2008 .

[20]  C. Borrego,et al.  Forest fire emissions in Portugal: a contribution to global warming? , 1994, Environmental pollution.

[21]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[22]  Russell K. Monson,et al.  Why are estimates of global terrestrial isoprene emissions so similar (and why is this not so for monoterpenes) , 2008 .

[23]  E. Fridell,et al.  Characterisation of particulate matter and gaseous emissions from a large ship diesel engine , 2009 .

[24]  David J. Diner,et al.  A data-mining approach to associating MISR smoke plume heights with MODIS fire measurements , 2007 .

[25]  Torben Mikkelsen,et al.  Ensemble dispersion forecasting—Part II: application and evaluation , 2004 .

[26]  B. Duncan,et al.  Vegetation fire emissions and their impact on air pollution and climate , 2009 .

[27]  Jaakko Kukkonen,et al.  A dispersion modelling system SILAM and its evaluation against ETEX data , 2006 .

[28]  Daniel Wang,et al.  Identification and characterization of inland ship plumes over Vancouver, BC , 2006 .

[29]  P. Bhave,et al.  Refining fire emissions for air quality modeling with remotely sensed fire counts: A wildfire case study , 2007 .

[30]  M. Jacobson GATOR-GCMM: A global through urban scale air pollution and weather forecast model , 2001 .

[31]  A L Robinson,et al.  Coupled partitioning, dilution, and chemical aging of semivolatile organics. , 2006, Environmental science & technology.

[32]  B. Reidya,et al.  Comparison of models used for national agricultural ammonia emission inventories in Europe : Liquid manure systems , 2007 .

[33]  William F. Ryan,et al.  A Real-Time Eulerian Photochemical Model Forecast System: Overview and Initial Ozone Forecast Performance in the Northeast U.S. Corridor , 2004 .

[34]  P. Manins,et al.  The Australian Air Quality Forecasting System. Part III: Case Study of a Melbourne 4-Day Photochemical Smog Event , 2004 .

[35]  Philippe Thunis,et al.  Skill and uncertainty of a regional air quality model ensemble , 2009 .

[36]  A. Robinson,et al.  Modeling semivolatile organic aerosol mass emissions from combustion systems. , 2006, Environmental science & technology.

[37]  Christer Johansson,et al.  Population exposure and mortality due to regional background PM in Europe - Long-term simulations of source region and shipping contributions , 2009 .

[38]  Ari Karppinen,et al.  Integrated Systems for Forecasting Urban Meteorology , Air Pollution and Population Exposure FUMAPEX , 2006 .

[39]  Archontoula Chaloulakou,et al.  Comparative assessment of neural networks and regression models for forecasting summertime ozone in Athens. , 2003, The Science of the total environment.

[40]  Cliff I. Davidson,et al.  An ammonia emission inventory for fertilizer application in the United States , 2003 .

[41]  Kaarle Kupiainen,et al.  Modeling carbonaceous aerosol over Europe: Analysis of the CARBOSOL and EMEP EC/OC campaigns , 2007 .

[42]  Laurent Menut,et al.  Does an Increase in Air Quality Models’ Resolution Bring Surface Ozone Concentrations Closer to Reality? , 2008 .

[43]  Predrag Hercog,et al.  Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations , 2009 .

[44]  C. Seigneur,et al.  Investigative modeling of new pathways for secondary organic aerosol formation , 2007 .

[45]  J. Dudhia A Nonhydrostatic Version of the Penn State–NCAR Mesoscale Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front , 1993 .

[46]  R. Friedrich,et al.  Effective pollutant emission heights for atmospheric transport modelling based on real-world information. , 2009, Environmental pollution.

[47]  Christine Wiedinmyer,et al.  Wildfire particulate matter in Europe during summer 2003: meso-scale modeling of smoke emissions, transport and radiative effects , 2007 .

[48]  Xiaoyang Zhang,et al.  Estimating emissions from fires in North America for air quality modeling , 2006 .

[49]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[50]  Adrian Sandu,et al.  The adjoint of CMAQ. , 2007, Environmental science & technology.

[51]  A. Bouwman,et al.  A 1990 global emission inventory of anthropogenic sources of carbon monoxide on 1° × 1° developed in the framework of EDGAR/GEIA , 1999 .

[52]  S. Solberg,et al.  Atmospheric Chemistry and Physics , 2002 .

[53]  R. Simpson,et al.  Forecasting peak ozone levels , 1983 .

[54]  E. Davakisa,et al.  Data assimilation in meteorological pre-processors : Effects on atmospheric dispersion simulations , 2007 .

[55]  Baoning Zhang,et al.  Models for gas/particle partitioning, transformation and air/water surface exchange of PCBs and PCDD/Fs in CMAQ , 2007 .

[56]  Renske Timmermans,et al.  The LOTOS?EUROS model: description, validation and latest developments , 2008 .

[57]  Philippe Thunis,et al.  Evaluation and intercomparison of Ozone and PM10 simulations by several chemistry transport models over four European cities within the CityDelta project , 2007 .

[58]  R. Francey,et al.  Interannual growth rate variations of atmospheric CO2 and its δ13C, H2, CH4, and CO between 1992 and 1999 linked to biomass burning , 2002 .

[59]  J. Webb,et al.  Comparison of models used for national agricultural ammonia emission inventories in Europe: liquid manure systems , 2008 .

[60]  E. Pattey,et al.  Improved temporal resolution in process-based modelling of agricultural soil ammonia emissions , 2008 .

[61]  Robert Vautard,et al.  Photochemical regimes in urban atmospheres: The influence of dispersion , 2000 .

[62]  J. Sodeau,et al.  Sources of ambient concentrations and chemical composition of PM2.5–0.1 in Cork Harbour, Ireland , 2010 .

[63]  M. Sofiev,et al.  Ensemble dispersion forecasting—Part I: concept, approach and indicators , 2004 .

[64]  Brian K. Lamb,et al.  A Numerical Daily Air Quality Forecast System for The Pacific Northwest , 2004 .

[65]  Gina Solomon,et al.  Pollution prevention at ports: clearing the air , 2004 .

[66]  Claudio Carnevale,et al.  Sensitivity of CTM simulations to meteorological input , 2005 .

[67]  Laurent Menut,et al.  Impact of large scale circulation on European summer surface ozone and consequences for modelling forecast , 2009 .

[68]  Vigdis Vestreng,et al.  Review and Revision. Emission data reported to CLRTAP. MSC-W Status Report 2003. , 2003 .

[69]  F. Meleux,et al.  Prev'air: An Operational Forecasting and Mapping System for Air Quality in Europe , 2009 .

[70]  G. Ancellet,et al.  Observed and modelled “chemical weather” during ESCOMPTE , 2005 .

[71]  A. Clappier,et al.  Towards improving the simulation of meteorological fields in urban areas through updated/advanced surface fluxes description , 2008 .

[72]  Laurent Menut,et al.  Submitted version: june 2008 Previsibility of mineral dust concentrations: The CHIMERE-DUST forecast during the first AMMA experiment dry season , 2008 .

[73]  Mian Chin,et al.  Long-term simulation of global dust distribution with the GOCART model: correlation with North Atlantic Oscillation , 2004, Environ. Model. Softw..

[74]  Michael J Kleeman,et al.  Measurement of emissions from air pollution sources. 5. C1-C32 organic compounds from gasoline-powered motor vehicles. , 2002, Environmental science & technology.

[75]  C. Spyrou,et al.  Long-range transport of anthropogenically and naturally produced particulate matter in the mediterranean and North Atlantic : Current state of knowledge , 2007 .

[76]  R. Rotunno,et al.  Effects of Moist Convection on Mesoscale Predictability , 2003 .

[77]  G. Briggs,et al.  ME 8E – SOME RECENT ANALYSES OF PLUME RISE OBSERVATION: DES ANALYSES RECENTES DES OBSERVATIONS DE PANACHE MONTANTE , 1971 .

[78]  Nadège Blond,et al.  Three-dimensional ozone analyses and their use for short-term ozone forecasts , 2004 .

[79]  H. Chepfer,et al.  Comparison of mineral dust layers vertical structures modeled with CHIMERE‐DUST and observed with the CALIOP lidar , 2009 .

[80]  Ingo Jacobsen,et al.  Comparison of Five Eulerian Air Pollution Forecasting Systems for the Summer of 1999 Using the German Ozone Monitoring Data , 2002 .

[81]  Robert Vautard,et al.  Validation of a hybrid forecasting system for the ozone concentrations over the Paris area , 2001 .

[82]  John Carras,et al.  The Australian Air Quality Forecasting System. Part I: Project Description and Early Outcomes , 2004 .

[83]  R. Vautard,et al.  CityDelta: A model intercomparison study to explore the impact of emission reductions in European cities in 2010 , 2007 .

[84]  Gabriele Curci,et al.  Modelling study of the impact of isoprene and terpene biogenic emissions on European ozone levels , 2009 .

[85]  Scott M. Robeson,et al.  Evaluation and comparison of statistical forecast models for daily maximum ozone concentrations , 1990 .

[86]  Jordan G. Powers,et al.  A Description of the Advanced Research WRF Version 2 , 2005 .

[87]  John P. Burrows,et al.  Inverse modelling of the spatial distribution of NO x emissions on a continental scale using satellite data , 2005 .

[88]  Srinath Krishnan,et al.  Modeling agricultural air quality: Current status, major challenges, and outlook , 2008 .

[89]  G. Baumbach,et al.  Neural modelling of the spatial distribution of air pollutants , 2009 .

[90]  Fuqing Zhang,et al.  Impacts of meteorological uncertainties on ozone pollution predictability estimated through meteorological and photochemical ensemble forecasts , 2007 .

[91]  Philippe Thunis,et al.  Evaluation of long-term ozone simulations from seven regional air quality models and their ensemble , 2007 .

[92]  R. H. Maryon,et al.  Validation of the UK Met. Office’s name model against the ETEX dataset , 1998 .

[93]  Allen L Robinson,et al.  Rethinking Organic Aerosols: Semivolatile Emissions and Photochemical Aging , 2007, Science.

[94]  Emil M. Constantinescu,et al.  Assessment of ensemble-based chemical data assimilation in an idealized setting , 2007 .

[95]  Hendrik Elbern,et al.  Ozone episode analysis by four-dimensional variational chemistry data assimilation , 2001 .