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Operational model evaluation for participate matter in Europe and North America in the context of AQMEII

机译：在AQMEII中对欧洲和北美参与事项的运营模型评估

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摘要

Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental-scale domains in North America and Europe for full-year simulations of 2006 in the context of Air Quality Model Evaluation International Initiative (AQMEII), whose main goals are model inter-comparison and evaluation. Standardised modeling outputs from each group have been shared on the web-distributed ENSEMBLE system, which allows statistical and ensemble analyses to be performed. In this study, the one-year model simulations are inter-compared and evaluated with a large set of observations for ground-level paniculate matter (PM_(10) and PM_(2.4) and its chemical components. Modeled concentrations of gaseous PM precursors, SO_2 and NO_2, have also been evaluated against observational data for both continents. Furthermore, modeled deposition (dry and wet) and emissions of several species relevant to PM are also inter-compared. The unprecedented scale of the exercise (two continents, one full year, fifteen modeling groups) allows for a detailed description of AQ model skill and uncertainty with respect to PM.Analyses of PM_(10) yearly time series and mean diurnal cycle show a large underestimation throughout the year for the AQ models included in AQMEII. The possible causes of PM bias, including errors in the emissions and meteorological inputs (e.g., wind speed and precipitation), and the calculated deposition are investigated. Further analysis of the coarse PM components, PM_(2.5) and its major components (SO_4,NH_4, NO_3, elemental carbon), have also been performed, and the model performance for each component evaluated against measurements. Finally, the ability of the models to capture high PM concentrations has been evaluated by examining two separate PM_(2.5) episodes in Europe and North America. A large variability among models in predicting emissions, deposition, and concentration of PM and its precursors during the episodes has been found. Major challenges still remain with regards to identifying and eliminating the sources of PM bias in the models. Although PM_(2.5) was found to be much better estimated by the models than PM10, no model was found to consistently match the observations for all locations throughout the entire year.
机译：在国际空气质量模型评估倡议（AQMEII）的背景下，已将十个最先进的区域空气质量（AQ）建模系统应用于北美和欧洲的陆域范围，以进行2006年的全年模拟，其主要目标是模型比较和评估。来自每个组的标准化建模输出已在网络分发的ENSEMBLE系统上共享，该系统允许执行统计和整体分析。在这项研究中，对一年模型模拟进行了比较和评估，并获得了对地面颗粒物（PM_（10）和PM_（2.4）及其化学成分）的大量观测结果。还根据两大洲的观测数据对SO_2和NO_2进行了评估，此外，还比较了与PM相关的几种物种的模拟沉积（干，湿）和排放情况。一年中，有15个模型组可以详细描述AQ模型的技能和关于PM的不确定性。对PM_（10）的年度时间序列和平均昼夜周期的分析表明，AQMEII中包含的AQ模型全年都被低估了。研究了PM偏差的可能原因，包括排放和气象输入（例如风速和降水）中的误差以及计算出的沉积物。还执行了污染物PM_（2.5）及其主要成分（SO_4，NH_4，NO_3，元素碳），并根据测量结果评估了每种成分的模型性能。最后，通过检查欧洲和北美的两个单独的PM_（2.5）事件，评估了模型捕获高PM浓度的能力。已经发现模型在预测发作期间PM及其前体的排放，沉积和浓度方面存在很大差异。在确定和消除模型中PM偏倚的来源方面，仍然存在重大挑战。尽管通过模型发现PM_（2.5）的估计要好于PM10，但没有模型能够与全年的所有位置的观测值保持一致。

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  • 来源
    《Atmospheric environment》 |2012年第6期|p.75-92|共18页
  • 作者

    Efisio Solazzo; Roberto Bianconi; Guido Pirovano; Volker Matthias; Robert Vautard; Michael D. Moran; K. Wyat Appel; Bertrand Bessagnet; Jørgen Brandt; Jesper H. Christensen; Charles Chemel; Isabelle Coll; Joana Ferreira; Renate Forkel; Xavier V. Francis; Georg Grell; Paola Grossi; Ayoe B. Hansen; Ana Isabel Miranda; Uarporn Nopmongcol; Marje Prank; Karine N. Sartelet; Martijn Schaap; Jeremy D. Silver; Ranjeet S. Sokhi; Julius Vira; Johannes Werhahn; Ralf Wolke; Greg Yarwood; Junhua Zhang; S. Trivikrama Rao; Stefano Galmarini;

  • 作者单位

    Institure for Environment and Sustainability, Joint Research Centre, European Commission, 1SPRA, Italy;

    Enviroware srl, Concorezzo (MB), itoly;

    INERIS, National Institute for Industrial Environment and Risks, Pare Technologique AIATA, 60550 Verneuil en Halatte, France,Ricerca sul Sistema Energetico (RSE SpA), Milano, Italy;

    Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geeshacht, Germany;

    IPSL/LSCE Laboratoire CEA/CNRS/UVSQ, France;

    Air Quality Research Division, Science and Technology Branch, Environment Canada, Toronto, Canada;

    Atmospheric Modeling and Analysis Division, Environmental Protection Agency, NC, USA;

    INERIS, National Institute for Industrial Environment and Risks, Pare Technologique AIATA, 60550 Verneuil en Halatte, France;

    Department of Environmental Science, Faculty of Science and Technology, Aarhus University, Denmark;

    Department of Environmental Science, Faculty of Science and Technology, Aarhus University, Denmark;

    National Centre for Atmospheric Science (NCAS), University of Hertfordshire, Hatfield, UK,Centre for Atmospheric & Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, UK;

    IPSL/L1SA UMR CNRS 7583, Universite Paris Est Creteil et Universite Paris Diderot, France;

    CESAM & Department of Environment and Planning, University of Aveiro, Aveiro, Portugal;

    IMK-IFU, Institute for Meteorology and Climate Research of the Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany;

    Centre for Atmospheric & Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, UK;

    NOAA/ESRL/GSD National Oceanic and Atmospheric Administration Environmental Systems Research Laboratory Global Systems Division Boulder, Colorado, CO, USA;

    Enviroware srl, Concorezzo (MB), itoly;

    Department of Environmental Science, Faculty of Science and Technology, Aarhus University, Denmark;

    CESAM & Department of Environment and Planning, University of Aveiro, Aveiro, Portugal;

    Environ International Corporation, Novato CA, USA;

    Finnish Meteorological Institute, Helsinki, Finland;

    CEREA, joint laboratory Ecole des Ponts ParisTech/ EDF R&D, Universite Paris-Est, France;

    Netherlands Organization for Applied Scientific Research (TNO), Utrecht, The Netherlands;

    Department of Environmental Science, Faculty of Science and Technology, Aarhus University, Denmark;

    Centre for Atmospheric & Instrumentation Research (CAIR), University of Hertfordshire, Hatfield, UK;

    Finnish Meteorological Institute, Helsinki, Finland;

    IMK-IFU, Institute for Meteorology and Climate Research of the Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany;

    Leibniz Institute for Tropospheric Research, Leipzig, Germany;

    Environ International Corporation, Novato CA, USA;

    Air Quality Research Division, Science and Technology Branch, Environment Canada, Toronto, Canada;

    Atmospheric Modeling and Analysis Division, Environmental Protection Agency, NC, USA;

    Institure for Environment and Sustainability, Joint Research Centre, European Commission, 1SPRA, Italy;

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  • 正文语种 eng
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  • 关键词

    AQMEII; regional air quality model; paniculate matter; model evaluation; PM_(2.5) speciation;

    机译：AQMEII;区域空气质量模型;颗粒状的物质模型评估;PM_（2.5）形态;

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