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Investigating the role of chemical and physical processes on organic aerosol modelling with CAMx in the Po Valley during a winter episode

机译:在冬季期间,调查化学过程和物理过程在CAM Valley中使用CAMx进行有机气溶胶建模的作用

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摘要

Traditional aerosol mechanisms underestimate the observed organic aerosol concentration, especially due to the lack of information on secondary organic aerosol (SOA) formation and processing. In this study we evaluate the chemical and transport model CAMx during a one-month in winter (February 2013) over a 5 km resolution domain, covering the whole Po valley (Northern Italy). This works aims at investigating the effects of chemical and physical atmospheric processing on modelling results and, in particular, to evaluate the CAMx sensitivity to organic aerosol (OA) modelling schemes: we will compare the recent 1.5D-VBS algorithm (CAMx-VBS) with the traditional Odum 2-product model (CAMx-SOAP). Additionally, the thorough diagnostic analysis of the reproduction of meteorology, precursors and aerosol components was intended to point put strength and weaknesses of the modelling system and address its improvement. Firstly, we evaluate model performance for criteria PM concentration. PM10 concentration was underestimated both by CAMx-SOAP and even more by CAMx-VBS, with the latter showing a bias ranging between -4.7 and -7.1 mu g m(-3). PM2.5 model performance was to some extent better than PM10, showing a mean bias ranging between -0.5 mu g m(-3) at rural sites and -5.5 mu g m(-3) at urban and suburban sites. CAMx performance for OA was clearly worse than for the other PM compounds (negative bias ranging between -40% and -75%). The comparisons of model results with OA sources (identified by PMF analysis) shows that the VBS scheme underestimates freshly emitted organic aerosol while SOAP overestimates. The VBS scheme correctly reproduces biomass burning (BBOA) contributions to primary OA concentrations (POA). In contrast VBS slightly underestimates the contribution from fossil-fuel combustion (HOA), indicating that POA emissions related to road transport are either underestimated or associated to higher volatility classes. The VBS scheme under-predictes the SOA too, but to a lesser extent than CAMx-SOAP. SOA underestimation can be related to corresponding underestimation of either aging processes or precursor emissions. This indicates that improvements in the emission inventories for semi and intermediate-volatility organic compounds are needed for further progress in this area. Finally, the comparison between modelled and observed SOA sources points out the urgency to include processing of OA in particle water phase into SOA formation mechanisms, to reconcile model results and observations. (C) 2017 Elsevier Ltd. All rights reserved.
机译:传统的气溶胶机制低估了观察到的有机气溶胶浓度,特别是由于缺乏有关次生有机气溶胶(SOA)形成和加工的信息。在这项研究中,我们评估了冬季(2013年2月)一个月(5个月)在5 km分辨率范围内的化学和运输模型CAMx,该模型覆盖了整个波河谷(意大利北部)。这项工作旨在调查化学和物理大气处理对建模结果的影响,尤其是评估CAMx对有机气溶胶(OA)建模方案的敏感性:我们将比较最近的1.5D-VBS算法(CAMx-VBS)与传统的Odum 2产品模型(CAMx-SOAP)。此外,对气象,前兆和气溶胶成分的复制进行全面的诊断分析,目的是指出建模系统的优点和缺点并解决其改进问题。首先,我们评估标准PM浓度的模型性能。 CAMx-SOAP都低估了PM10的浓度,而CAMx-VBS甚至低估了PM10的浓度,后者的偏倚介于-4.7和-7.1μg m(-3)之间。 PM2.5模型的性能在一定程度上要优于PM10,显示出的平均偏差在农村站点为-0.5μg m(-3),在城市和郊区站点为-5.5μg m(-3)。 OA的CAMx性能显然比其他PM化合物差(负偏差范围在-40%和-75%之间)。模型结果与OA来源(通过PMF分析确定)的比较表明,VBS方案低估了新鲜排放的有机气溶胶,而SOAP高估了。 VBS计划正确地再现了生物质燃烧(BBOA)对主要OA浓度(POA)的贡献。相比之下,VBS稍微低估了化石燃料燃烧(HOA)的贡献,表明与公路运输相关的POA排放要么被低估,要么与较高的挥发性等级相关。 VBS方案也预测SOA,但程度要低于CAMx-SOAP。 SOA低估可能与老化过程或前体排放的相应低估有关。这表明需要进一步提高半挥发性和中等挥发性有机化合物的排放清单。最后,在模拟和观察到的SOA来源之间的比较指出,迫切需要将颗粒水相中的OA处理纳入SOA形成机制中,以协调模型结果和观察结果。 (C)2017 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Atmospheric environment》 |2017年第12期|126-142|共17页
  • 作者单位

    Politecn Milan, Dipartimento Ingn Civile & Ambientale, I-20133 Milan, Italy|Ric Sistema Energet RSE SpA, Via Rubattino 54, I-20134 Milan, Italy;

    Ric Sistema Energet RSE SpA, Via Rubattino 54, I-20134 Milan, Italy;

    CNR, ISAT, I-40129 Bologna, Italy;

    Politecn Milan, Dipartimento Ingn Civile & Ambientale, I-20133 Milan, Italy;

    ARPA Lombardia, Settore Monitoraggi Ambientali, I-20129 Milan, Italy;

    ARPA Lombardia, Settore Monitoraggi Ambientali, I-20129 Milan, Italy;

    CNR, ISAT, I-40129 Bologna, Italy;

    ARPAE Emilia Romagna, CTR Aree Urbane, I-40122 Bologna, Italy;

    Ric Sistema Energet RSE SpA, Via Rubattino 54, I-20134 Milan, Italy;

    Ric Sistema Energet RSE SpA, Via Rubattino 54, I-20134 Milan, Italy;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Organic aerosol modelling; CAMx; AMS; Positive matrix factorization; Po Valley;

    机译:有机气溶胶建模CAMx AMS正矩阵分解普谷;

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