Review: Untangling the influence of air-mass history in interpreting observed atmospheric composition

被引:287
作者
Fleming, Zoe L. [1 ]
Monks, Paul S.
Manning, Alistair J. [2 ]
机构
[1] Univ Leicester, Dept Chem, NCAS, Leicester LE1 7RH, Leics, England
[2] Met Off, Exeter EX1 3PB, Devon, England
关键词
Air mass; Trajectory; Dispersion model; Composition; LONG-RANGE TRANSPORT; POSITIVE MATRIX FACTORIZATION; PARTICLE DISPERSION MODEL; SOURCE-RECEPTOR RELATIONSHIPS; BACK-TRAJECTORY ANALYSIS; AEROSOL OPTICAL-PROPERTIES; POTENTIAL SOURCE LOCATIONS; NORTH-ATLANTIC OCEAN; CLUSTER-ANALYSIS; SURFACE OZONE;
D O I
10.1016/j.atmosres.2011.09.009
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Is wind direction an adequate marker of air mass history? This review looks at the evolution of methods for assessing the effect of the origin and pathway of air masses on composition change and trends. The composition of air masses and how they evolve and the changing contribution of sources and receptors are key elements in atmospheric science. Source receptor relationships of atmospheric composition can be investigated with back trajectory techniques, tracing forward from a defined geographical origin to arrive at measurement sites where the composition may have altered during transport. The distinction between the use of wind sector analysis, trajectory models and dispersion models to interpret composition measurements is explained and the advantages and disadvantages of each are illustrated with examples. Historical uses of wind roses, back trajectories and dispersion models are explained as well as the methods for grouping and clustering air masses. The interface of these methods to the corresponding chemistry measured at the receptor sites is explored. The review does not detail the meteorological derivation of trajectories or the complexity of the models but focus on their application and the statistical analyses used to compare them with in situ composition measurements. A newly developed methodology for analysing atmospheric observatory composition data according to air mass pathways calculated with the NAME dispersion model is given as a detailed case study. The steps in this methodology are explained with relevance to the Weyboume Atmospheric Observatory in the UK. (C) 2011 Elsevier BM. All rights reserved.
引用
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页码:1 / 39
页数:39
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