Universität zu Köln

Li, Zhuoqun (2014). Momentum and Mass Transfer from Atmosphere to Rough Surfaces: Improvement on Drag Partition Theory and Dry Deposition Model. PhD thesis, Universität zu Köln.

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Abstract

The transfers of momentum and mass from the atmosphere to rough surfaces are fundamental scientific problems for meteorology, environment and industry. The transfer of momentum is crucial for the transfer of mass, heat, etc., in the boundary layer. The mass transfer, e.g., dust dry deposition, is a key process of the dust cycle. Both processes are closely related, but not well understood, particularly on rough surfaces or in unsteady conditions. Momentum and mass flux have been found to be associated with the geometric dimensions of the wake behind roughness elements. The dimensions of these wakes can be determined by the geometry of the obstacles on rough surfaces and wind speed. The objective of this thesis is to improve the theories of momentum transfer and drag partition between roughness elements and the exposed underlying surface, as well as the parameterization of particle deposition by means of numerical simulations of the air flow and dust flux over rough surfaces. To investigate the transfer of momentum and mass to rough surfaces, both two-dimensional Reynold Stress Model (2D RSM) simulations and three-dimensional Large Eddy Simulations (3D LES) are carried out. A rough surface in the simulation refers to a flat surface with regularly distributed identical roughness elements. The wind profile, surface drag, and the geometric dimensions of the wake are determined from the simulation results. Friction velocity (u*) and a friction coefficient (u*/uh) are estimated as functions of roughness density (λ), threshold roughness density (λa), and wind speed (ur). The dimensions of the wake, which influence the drag and are controlled by wind speed, are subject to the roughness density and the dimensions of the elements. Hence, it is important to repeat the numerical experiments for various element heights (h), roughness densities and wind speeds. To study dust dry deposition, particle injections are included in the 3D simulation. It allows for particle tracking in the turbulent flow; thereby, the deposition velocity can be determined under different wind speeds, particle diameters and roughness densities. The 2D simulation consists of 260 runs on 13 distinctive surfaces (1/30 < λ < 2/3, h = 5, 7.5 and 10 mm) at 20 different wind speeds (1 - 20 ms-1). The purpose of the 2D simulation is to analyze the geometric dimensions of the wake in the absence of spanwise disturbance. 2D simulations limit the possible mutual sheltering of elements in the streamwise direction. Without these disturbances, the length of the wake behind isolated element is presented as a function of wind speed. The height-to-length ratio of the wake (λw = hw/Lw) is analyzed and found to be independent of element height. When the wake is a full wake, λw is also independent from wind speed, and λw = λa. The relation among the dimensions of roughness elements, the wake and the drag are estimated. A physical model of drag and drag partition is proposed, based on a resistance method. The drag and drag partitions are expressed as functions of λ, and λa, without empirical parameters. The estimation of the new model are analyzed and compared to classical experimental results and a 3D simulations results. The 3D simulation for air flow over rough surface are conducted for 11 distinctive surfaces (1/30 < λ < 1/2) with identical elements of 10 mm height, at 6 different wind speeds (1-25 ms-1). In the resistance method for the momentum flux, the resistances of the element (Rr), and the underlying surface (Rs) in the canyon layer are respectively determined. The threshold roughness density (λa) is introduced in the expressions of resistances. This threshold is defined as the roughness density of the surface which has equal momentum flux on the element and on the underlying surface. This threshold can be determined by the length of the wake (Lw) on rough surfaces and helps to distinguish elements of different length-to-height ratios (b/h). New expressions of friction velocity and drag partitions (τr + τs) are derived without any empirical parameter. The friction coefficient is determined empirically. Classical wind tunnel data of drag for rough surfaces with various roughness densities, and results from the 3D simulation are successfully reproduced, and in response to different length-to-height ratios of roughness elements. Thus, the new expressions of drag and drag partition on rough surfaces are validated. The discrepancy between the estimation of existing dry deposition model and field measurements reaches 2 orders of magnitude. In the existing models of dust dry deposition, the rough surfaces are treated as a single cylinder. Sensitivity tests show that the possible uncertainty on the deposition velocity generated by this method can reach 337%. To investigate dust dry deposition in more details, 3D simulations of deposition on rough surfaces are conducted and 15 groups of particles with different diameters (0.1 μm < dp < 10 μm) are injected into the simulation domain. Deposition velocity is deduced by counting trapped particle on the surfaces, in fully developed flow. Regression analysis is applied to fit the deposition velocity as functions of wind speed, roughness density or particle size from simulation results. The resulting prediction of the deposition velocity is consistent with field measurements and explains the discrepancies among existing field measurements and previous model estimations. The measurement of deposition process in the natural flow is also studied. The aim of this part is to examine the influence of unsteady dust flux on the measurement of deposition velocity and errors caused by field measuring method. An existing vertical dispersion framework is introduced to simulate the one-dimensional deposition velocity. Intermittent dust flux data from a well-known field measurement during a dust event, as input data. The resulting estimations of deposition velocity are consistent with field measurements. The understanding of momentum and mass transfer on rough surfaces could thereby be improved.

Item Type:	Thesis (PhD thesis)
Translated abstract:	Abstract Language Der Impuls- und Massenfluss zwischen Atmosphäre und Bodenoberfläche stellt ein wichtiges wissenschaftliches Problem dar, das von entscheidender Bedeutung für Meteorologie, Umwelt und Industrie ist. Der Transfer von Impuls ist entscheidend für den Transport von Masse, Wärme, etc. in der Grenzschicht und der Transfer von Masse, z.B. die trockene Deposition von Staubpartikeln, ist ein Schlüsselprozess des Staubkreislaufs. Beide Prozesse sind eng miteinander verknüpft, aber insbesondere auf rauen Oberflächen oder in ungleichförmigen Strömungsbedingungen noch nicht gut verstanden. Impuls- und Massenflüsse konnten mit den geometrischen Dimensionen der Nachlaufströmung hinter Rauigkeitselementen in Zusammenhang gebracht werden. Die Dimension dieser Nachlaufströmung hängt mit der Geometrie der rauen Oberfläche sowie der Windgeschwindigkeit zusammen. Das Ziel dieser Arbeit ist es, die Theorien zu Impulsfluss und dessen Partitionierung zwischen Rauigkeitselementen und exponierten Oberflächen sowie die Parametrisierung der Partikeldeposition mit Hilfe von numerischen Simulationen der Strömung und des Staubflusses auf rauen Oberflächen zu verbessern. Um den Transport von Impuls und Masse auf raue Oberflächen zu untersuchen, werden sowohl zweidimensionale Simulationen mit dem sogenannten „Reynolds Stress Model“ (2D RSM) als auch dreidimensionale „Large-Eddy“ Simulationen (3D LES) durchgeführt. Die Bezeichnung „raue Oberfläche“ bezieht sich in den Simulationen auf eine flache Oberfläche auf der identische Rauigkeitselemente gleichmäßig verteilt sind. Das Windprofil, die Bodenschubspannung und die geometrischen Dimensionen der Nachlaufströmung werden an Hand der Simulationsergebnisse bestimmt. Die Schubspannungsgeschwindigkeit (u*) und der Schubspannungskoeffizient (u*/uh) werden in Abhängigkeit von Rauigkeitsdichte (λ), Grenzwert der Rauigkeitsdichte (λa) und Windgeschwindigkeit (ur) bestimmt. Die Dimensionen der Nachlaufströmung hängen von der Windgeschwindigkeit ab und beeinflussen die Schubspannung. Sie werden durch die Rauigkeitsdichte sowie Form und Größe der Rauigkeitslemente bestimmt. Daher ist es wichtig die numerischen Experimente für unterschiedliche Elementhöhen (h), Rauigkeitsdichten und Windgeschwindigkeiten zu wiederholen. Zur Untersuchung der trockenen Staubdeposition wird die 3D Simulation um eine Partikelinjektion erweitert. Dies ermöglicht die Verfolgung der Partikelbahn in der turbulenten Strömung. Dadurch kann die Depositionsgeschwindigkeit für verschiedene Windgeschwindigkeiten, Partikeldurchmesser und Rauigkeitsdichten bestimmt werden. Die 2D Simulation besteht aus 260 Läufen für 13 bestimme Oberflächen (1/30 < λ < 2/3, h = 5, 7.5 und 10 cm) bei 20 Windgeschwindigkeiten (1 - 20 m/s). Der Zweck der 2D Simulation ist die Analyse der geometrischen Dimensionen der Nachlaufströmung in Abwesenheit einer Störung quer zur Strömungsrichtung. 2D Simulationen begrenzen die gegenseitige Abschirmung der Rauigkeitselemente in Strömungsrichtung. Ohne diese Störungen kann die Größe der Nachlaufströmung als Funktion der Windgeschwindigkeit beschrieben werden. Die Analyse des Verhältnisses zwischen Höhe und Länge der Nachlaufströmung (λw = 1/Lw) zeigt keine Abhängigkeit zur Höhe der Rauigkeitelemente und der Windgeschwindigkeit. Und λw=λa. Der Zusammenhang zwischen den Dimensionen der Bodenoberfläche, der Nachlaufströmung und der Schubspannung wird bestimmt. Ein physikalisches Modell für Schubspannung und Schubspannungspartitionierung wird basierend auf einer Widerstandsmethode erstellt. Schubspannung und Schubspannungspartitionierung werden als Funktionen von λ und λa ohne empirische Parameter dargestellt. Die Ergebnisse des neuen Modells werden analysiert und verglichen mit denen klassischer Experimente und eines 3D Simulationsmodells. Die 3D-Simulationen werden für 11 Oberflächen (1/30 < λ < 1/2) mit identischen Elementen von 10 mm Höhe für 6 Windgeschwindigkeiten (1 - 25 m/s) durchgeführt. In der Widerstandsmethode für den Impulsflusswerden die Widerstände des Elementes (Rr) und der Bodenoberfläche (Rs) in den Elementzwischenräumen werden bestimmt. Der Grenzwert der Rauigkeitsdichte (λa) wird zur Beschreibung der genannten Widerstände genutzt. Der Grenzwert ist definiert als die Rauigkeitsdichte des Bodens, bei dem der gleiche Impulsfluss auf das Rauigkeitselement und die Bodenoberfläche vorherrscht. Der Grenzwert kann durch die Länge der Nachlaufströmung (Lw) auf rauen Oberflächen bestimmt werden und dient der Unterscheidung von Elementen mit unterschiedlichem Verhältnis Länge/Höhe. Neue Ausdrücke für den Schubspannungskoeffizienten und die Schubspannungspartitionierung (τr+τs) konnten ohne empirische Parameter bestimmt werden. Der Reibungskoeffizient wurde empirisch bestimmt. So konnten klassische Windtunneldaten für raue Oberflächen mit unterschiedlichen Rauigkeitsdichten und verschiedenen Elementlänge/-höhe Verhältnissen erfolgreich reproduziert werden. Dadurch konnten die neuen Ausdrücke für Schubspannung und Schubspannungsunterteilung auf rauen Oberflächen validiert werden. Die Diskrepanz zwischen bestehenden Depositionsmodellen und Feldmessungen beträgt bis zu zwei Größenordnungen. In existierenden Modellen der trockenen Deposition werden raue Oberflächen als separate Zylinder behandelt. Sensitivitätstests zeigen, dass die durch diese Methode bestimmte Depositionsgeschwindigkeit mit einer Unsicherheit von bis zu 337% behaftet ist. Zur detaillierteren Untersuchung der trockenen Deposition werden in dieser Studie 3D Simulationen der Deposition auf rauen Oberflächen durchgeführt. Hierzu werden 15 Gruppen von Partikeln mit unterschiedlichen Durchmessern (0.1μm < dp < 10μm) in die Simulationsdomäne injiziert. Rückschlüsse auf die Depositionsgeschwindigkeit können mit Hilfe der Anzahl der Partikel gezogen werden, die sich auf der Oberfläche bei vollentwickelter Strömung niederschlagen. Die Depositionsgeschwindigkeit kann schließlich durch Regression als Funktion von Windgeschwindigkeit, Rauigkeitsdichte oder Partikelgröße an Hand der Simulationsergebnisse bestimmt werden. Die daraus folgende Vorhersage der Depositionsgeschwindigkeit ist konsistent mit Feldmessungen und erklärt den Unterschied zwischen Beobachtungen und Ergebnissen bestehender Modelle. Der Einfluss der natürlichen Strömungen auf den Depositionsprozess wird ebenfalls untersucht. Ziel davon ist es den Einfluss des unstetigen Staubflusses auf die gemessene Depositionsgeschwindigkeit sowie Fehler durch die Methode bei Feldmessungen zu prüfen. Hierzu wird eine existierende Beschreibung der vertikalen Dispersion zur Simulation der eindimensionalen Depositionsgeschwindigkeit genutzt. Input hierfür ist der intermittierende Staubfluss eines weitbekannten Feldexperimentes während eines Staubereignisses. Die damit geschätzte Depositionsgeschwindigkeit ist konsistent mit den Feldmessungen. Somit konnte das Verständnis von Impuls- und Massenfluss auf rauen Oberflächen verbessert werden. German
Creators:	Creators Email ORCID ORCID Put Code Li, Zhuoqun zli83110@gmail.com UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-59387
Date:	17 November 2014
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Geosciences > Institute for Geophysics and Meteorology
Subjects:	Natural sciences and mathematics Earth sciences
Uncontrolled Keywords:	Keywords Language Drag partition UNSPECIFIED Dry deposition UNSPECIFIED Momentum transfer UNSPECIFIED Wake UNSPECIFIED Flow structure UNSPECIFIED
Date of oral exam:	14 January 2015
Referee:	Name Academic Title Shao, Yaping Prof. Dr. Kerschgens, Michael Prof. Dr.
References:	Ahmadi, G., and S. J. Chowdhury (1991) A rate-dependent algebraic stress model for turbulence. Applied Mathematical Modelling 15: 516-524. Bache, D. (1979) Particulate transport within plant canopies—II. Prediction of deposition velocities. Atmospheric Environment (1967) 13: 1681-1687. Batchelor, G. (1970) An Introduction to Fluid Dynamics. Cambridge University Press. Belot, Y., A. Baille, and J. L. Delmas (1976) Modele numerique de dispersion des polluants atmospheriques en presence de couverts vegetaux: Application aux couverts forestiers. Atmospheric Environment (1967) 10: 89-98. Beswick, K., K. Hargreaves, M. Gallagher, T. Choularton, and D. Fowler (1991) Size‐resolved measurements of cloud droplet deposition velocity to a forest canopy using an eddy correlation technique. Quarterly Journal of the Royal Meteorological Society 117: 623-645. Brown, S., W. G. Nickling, and J. a. Gillies (2008) A wind tunnel examination of shear stress partitioning for an assortment of surface roughness distributions. Journal of Geophysical Research 113: F02S06. Brutsaert, W. (1975) The roughness length for water vapor sensible heat, and other scalars. Journal of the Atmospheric Sciences 32: 2028-2031. Chamberlain, A. (1953) Aspects of travel and deposition of aerosol and vapour clouds. Chamberlain, A. A. C. (2012) Transport of gases to and from grass and grass-like surfaces Atomic Energy Researchl 290: 236-265. Chamberlain, a. C. (1967) Transport of Lycopodium Spores and Other Small Particles to Rough Surfaces. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 296: 45-70. Chamberlain, B. A. C., R. C. Chadwick, H. Physiccr, and M. Division (1966) Transport of iodine from atmosphere to ground. Cheng, H., and I. Castro (2002) Near wall flow over urban-like roughness. Boundary-Layer Meteorology 0: 229-259. Cheng, H., P. Hayden, a. G. Robins, and I. P. Castro (2007) Flow over cube arrays of different packing densities. Journal of Wind Engineering and Industrial Aerodynamics 95: 715-740. Christensen, J. H. (1997) The Danish Eulerian hemispheric model—A three-dimensional air pollution model used for the Arctic. Atmospheric Environment 31: 4169-4191. Chung, D., and D. I. Pullin (2009) Large-eddy simulation and wall modelling of turbulent channel flow. Journal of Fluid Mechanics 631: 281. Clifton, A., and M. Lehning (2008) Improvement and validation of a snow saltation model using wind tunnel measurements. Earth Surface Processes and Landforms 33: 2156-2173. Cowan, I. (1968) Mass, heat and momentum exchange between stands of plants and their atmospheric environment. Quarterly Journal of the Royal Meteorological Society 94: 523-544. Csanady, G. (1963) Turbulent diffusion of heavy particles in the atmosphere. Journal of the Atmospheric Sciences 20: 201-208. Davidson, C. I., and Y.-L. Wu (1990) Dry deposition of particles and vapors. Acidic precipitation, Springer, 103-216. Davies, J. T. (2012) Turbulence phenomena: an introduction to the eddy transfer of momentum, mass, and heat, particularly at interfaces. Elsevier. Davis, M. B. (1969) Climatic changes in southern Connecticut recorded by pollen deposition at Rogers Lake. Ecology: 409-422. Finnigan, J. (2000) Turbulence in plant canopies. Annual Review of Fluid Mechanics: 519-571. Friedlander, S., and H. Johnstone (1957) Deposition of suspended particles from turbulent gas streams. Industrial & Engineering Chemistry 49: 1151-1156. Frisch, U. (1995) Turbulence: the legacy of AN Kolmogorov. Cambridge university press. Fuchs, N. A. (1964) The mechanics of aerosols. Dover Publications. Gallagher, M., and Coauthors (1992) Measurements of aerosol exchange to Heather Moor. Proc. EUROTRAC Symp, 694-669. Gallagher, M. W., K. M. Beswick, J. Duyzer, H. Westrate, T. W. Choularton, and P. Hummelshøj (1997) Measurements of aerosol fluxes to speulderforest using a micrometeorological technique. Atmospheric Environment 31: 359-373. Garratt, J. (1977) Review of drag coefficients over oceans and continents. Monthly weather review 105: 915-929. Garratt, J. R. (1994) The atmospheric boundary layer. Cambridge university press, 316 pp. Gillies, J. A., W. G. Nickling, and J. King (2007) Shear stress partitioning in large patches of roughness in the atmospheric inertial sublayer. Boundary-Layer Meteorology 122: 367-396. Ginoux, P., J. Prospero, O. Torres, and M. Chin (2004) Long-term simulation of global dust distribution with the GOCART model: correlation with North Atlantic Oscillation. Environmental Modelling & Software 19: 113-128. Giorgi, F. (1986) A particle dry‐deposition parameterization scheme for use in tracer transport models. … of Geophysical Research: Atmospheres (1984–2012) 91: 9794-9806. Gong, S., L. Barrie, and J. P. Blanchet (1997) Modeling sea‐salt aerosols in the atmosphere: 1. Model development. Journal of Geophysical Research: Atmospheres (1984–2012) 102: 3805-3818. Gong, S., X. Zhang, T. Zhao, I. McKendry, D. Jaffe, and N. Lu (2003) Characterization of soil dust aerosol in China and its transport and distribution during 2001 ACE‐Asia: 2. Model simulation and validation. Journal of Geophysical Research: Atmospheres (1984–2012) 108. Gong, S. L., and L. A. Bartie (1997) Modeling sea-salt aerosols in the atmosphere. 102: 3805-3818. Grant, P. F., and W. G. Nickling (1998) Direct field measurement of wind drag on vegetation for application to windbreak design and modelling. Land Degradation & Development 9: 57-66. Grimmond, C., and T. R. Oke (1999a) Aerodynamic properties of urban areas derived from analysis of surface form. Journal of Applied Meteorology 38: 1262-1292. Grosch, S., and G. Schmitt (1988) Experimental investigations on the deposition of trace elements in forest areas. Environmental Meteorology, Springer, 201-216. Hall, D., R. Macdonald, and S. Walker (1996) Measurements of dispersion within simulated urban arrays: a small scale wind tunnel study. Building Research Establishment. Holmes, J. D. (2001) Wind loading of structures. CRC Press. Holsen, T. M., and K. E. Noll (1992) Dry deposition of atmospheric particles: application of current models to ambient data. Environmental Science & Technology 26: 1807-1815. Hussein, T., A. Hruška, P. Dohányosová, L. Džumbová, J. Hemerka, M. Kulmala, and J. Smolík (2009) Deposition rates on smooth surfaces and coagulation of aerosol particles inside a test chamber. Atmospheric Environment 43: 905-914. In, H.-J., and S.-U. Park (2002) A simulation of long-range transport of Yellow Sand observed in April 1998 in Korea. Atmospheric Environment 36: 4173-4187. Incropera, F. P. (2011) Fundamentals of heat and mass transfer. John Wiley & Sons, 1052 pp. Jarvis, P., G. James, and J. Landsberg (1976) Coniferous forest. Vegetation and the Atmosphere 2: 171-240. Joutsenoja, T. (1992) Measurements of aerosol deposition to a cereal crop. Choularton, T., éditeur, Measurements and modelling of gases and aerosols to complex terrain. Nat. Envir. Res. Counc., UK 45. Kastner-Klein, P., and M. W. Rotach (2004) Mean flow and turbulence characteristics in an urban roughness sublayer. Boundary-Layer Meteorology 111: 55-84. Kim, J. (1989) On the structure of pressure fluctuations in simulated turbulent channel flow. Journal of Fluid Mechanics 205: 421-451. Kouznetsov, R., and M. Sofiev (2012) A methodology for evaluation of vertical dispersion and dry deposition of atmospheric aerosols. Journal of Geophysical Research 117: D01202. Kreutzkam, B., C. Wieland, and H. Spliethoff (2012) Improved numerical prediction of ash formation and deposition using a novel developed char fragmentation model. Fuel 98: 103-110. Lai, a. C. K. (2002) Particle deposition indoors: a review. Indoor air 12: 211-214. Le, H., P. Moin, and J. Kim (1997) Direct numerical simulation of turbulent flow over a backward-facing step. Journal of Fluid Mechanics 330: 349-374. Leonardi, S., P. Orlandi, R. Smalley, L. Djenidi, and R. Antonia (2003) Direct numerical simulations of turbulent channel flow with transverse square bars on one wall. Journal of Fluid Mechanics 491: 229-238. Leuning, R., and P. M. Attiwill (1978) Mass, heat and momentum exchange between a mature eucalyptus forest and the atmosphere. Agricultural Meteorology 19: 215-241. Lighthill, J. (1975) Mathematical Biofluiddynamics. SIAM. Liu, B. Y. H., and J. K. Agarwal (1974) Experimental observation of aerosol deposition in turbulent flow. Journal of Aerosol Science 5: 145-155. Liu, C. K., S. Klein, and J. Johnston, 1966: An experimental study of turbulent boundary layer on rough walls. Lorenz, R., and C. Murphy Jr (1989) Dry deposition of particles to a pine plantation. Boundary-Layer Meteorology 46: 355-366. Luo, J.-p., Z.-m. Lu, and Y.-l. Liu (2009) Simulation of Lagrangian dispersion using a Lagrangian stochastic model and DNS in a turbulent channel flow. Journal of Hydrodynamics, Ser. B 21: 767-773. Macdonald, R. W., R. F. Griffiths, and D. J. Hall (1998a) A comparison of results from scaled field and wind tunnel modelling of dispersion in arrays of obstacles. Atmospheric Environment 32: 3845-3862. Macdonald, R. W., R. F. Griffiths, and D. J. Hall (1998b) An improved method for the estimation of surface roughness of obstacle arrays. Atmospheric Environment 32: 1857-1864. Mahowald, N., and Coauthors (1999) Dust sources and deposition during the last glacial maximum and current climate: A comparison of model results with paleodata from ice cores and marine sediments. Journal of Geophysical Research 104: 15895. Mahrt, L. (1989) Intermittent of atmospheric turbulence. Marshall, J. (1971) Drag measurements in roughness arrays of varying density and distribution. Agricultural Meteorology 8: 269-292. McLaughlin, J. B. (1989) Aerosol particle deposition in numerically simulated channel flow. Physics of Fluids A: Fluid Dynamics 1: 1211. Mulhearn, P., and J. Finnigan (1978) Turbulent flow over a very rough, random surface. Boundary-Layer Meteorology 15: 109-132. Musick, H., and D. Gillette (1990) Field evaluation of relationships between a vegetation structural parameter and sheltering against wind erosion. Land Degradation & Development 2: 87-94. Nickovic, S., G. Kallos, A. Papadopoulos, and O. Kakaliagou (2001) A model for prediction of desert dust cycle in the atmosphere. Journal of Geophysical Research: Atmospheres (1984–2012) 106: 18113-18129. Nikora, V., K. Koll, I. McEwan, S. McLean, and A. Dittrich (2004) Velocity Distribution in the Roughness Layer of Rough-Bed Flows. Journal of Hydraulic Engineering 130: 1036-1042. O'Loughlin, E. M. (1965) Resistance to flow over boundaries with small roughness concentrations. Dissertation. O'Loughlin, E. M., and V. S. Annambhotla (1969) Flow phenomena near rough boundaries. Journal of Hydraulic Research 7: 231-250. Owen, P. (1969) Pneumatic transport. Journal of Fluid Mechanics 39: 407-432. Owen, P., and W. Thomson (1963) Heat transfer across rough surfaces. Journal of Fluid Mechanics 15: 321-334. Paradisi, P., R. Cesari, a. Donateo, D. Contini, and P. Allegrini (2012) Scaling laws of diffusion and time intermittency generated by coherent structures in atmospheric turbulence. Nonlinear Processes in Geophysics 19: 113-126. Peters, K., and R. Eiden (1992) Modelling the dry deposition velocity of aerosol particles to a spruce forest. Atmospheric Environment. Part A. General Topics 26: 2555-2564. Petroff, A., A. Mailliat, M. Amielh, and F. Anselmet (2008) Aerosol dry deposition on vegetative canopies. Part I: Review of present knowledge. Atmospheric Environment 42: 3625-3653. Prandtl, L. (1963) The essentials of fluid dynamics. Blackie & Son Limited. Raupach, M., A. Thom, and I. Edwards (1980) A wind-tunnel study of turbulent flow close to regularly arrayed rough surfaces. Boundary-Layer Meteorology 18: 373-397. Raupach, M. R. (1992) Drag and drag partition on rough surfaces. Boundary-Layer Meteorology 60: 375-395. Ruijrok, W., C. Davidson, and W. Nicholson (1995) Dry deposition of particles. Tellus B. Schlichting, H. (1936) Experimentelle untersuchungen zum rauhigkeitsproblem. Archive of Applied Mechanics. Schlichting, H., and K. Gersten (2000) Boundary-layer theory. Springer, 812 pp. Sehmel, G., and W. Hodgson (1978) Model for predicting dry deposition of particles and gases to environmental surfaces. Sehmel, G. A. (1980) Particle and gas dry deposition: A review. Atmospheric Environment (1967) 14: 983-1011. Seinfeld, J. H., and S. N. Pandis (2012) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & Sons. Sellers, P. J., and Coauthors (1997) Modeling the Exchanges of Energy, Water, and Carbon Between Continents and the Atmosphere. Science 275: 502-509. Shao, Y. (2008) Physics and modelling of wind erosion. Vol. 37, Springer, 375 pp. Shao, Y., and Y. Yang (2005) A scheme for drag partition over rough surfaces. Atmospheric Environment 39: 7351-7361. Shao, Y., and Y. Yang (2008) A theory for drag partition over rough surfaces. Journal of Geophysical Research 113: F02S05. Shao, Y., and Coauthors (2003) Northeast Asian dust storms: Real‐time numerical prediction and validation. Journal of Geophysical Research: Atmospheres (1984–2012) 108. Shaw, R. H., and A. Pereira (1982) Aerodynamic roughness of a plant canopy: a numerical experiment. Agricultural Meteorology 26: 51-65. Shuttleworth, W. J., and Coauthors (1984) Eddy correlation measurements of energy partition for Amazonian forest. Quarterly Journal of the Royal Meteorological Society 110: 1143-1162. Simiu, E., and R. H. Scanlan (1996) Wind effects on structures. Wiley. Sini, J.-F., S. Anquetin, and P. G. Mestayer (1996) Pollutant dispersion and thermal effects in urban street canyons. Atmospheric Environment 30: 2659-2677. Slinn, S. a., and W. G. N. Slinn (1980) Predictions for particle deposition on natural waters. Atmospheric Environment (1967) 14: 1013-1016. Slinn, W. (1977) Some approximations for the wet and dry removal of particles and gases from the atmosphere. Water, Air, and Soil Pollution 7: 513-543. Slinn, W. (1982a) Predictions for particle deposition to vegetative canopies. Atmospheric Environment (1967) 16: 1785-1794. Stier, P., and Coauthors (2005) The aerosol-climate model ECHAM5-HAM. Atmospheric Chemistry and Physics 5: 1125-1156. Stone, B. M., and H. T. Shen (2002) Hydraulic resistance of flow in channels with cylindrical roughness. Journal of Hydraulic Engineering 128: 500-506. Stull, R. B. (1988) An introduction to boundary layer meteorology. Vol. 13, Springer. Tanaka, T. Y., and M. Chiba (2006) A numerical study of the contributions of dust source regions to the global dust budget. Global and Planetary Change 52: 88-104. Tegen, I. (2003) Modeling the mineral dust aerosol cycle in the climate system. Quaternary Science Reviews 22: 1821-1834. Thom (1967) The exchange of momentum, mass, and heat between an artificial leaf and the airflow in a wind-tunnel: 44-55. Thom, A. (1972a) Momentum, mass and heat exchange of vegetation. Quarterly Journal of the Royal Meteorological Society 98: 124-134. Thom, a. S. (1971) Momentum absorption by vegetation. Quarterly Journal of the Royal Meteorological Society 97: 414-428. THOM, A. S. (1972b) Momentum, mass and heat exchange of vegetation: 124-134. Thom, R. (1975) Structural stability and morphogenesis, 1975. Trans. by D. Fowler. Reading, Mass.: Benjamin. Uematsu, M., and Coauthors (2010) Atmospheric transport and deposition of anthropogenic substances from the Asia to the East China Sea. Marine Chemistry 120: 108-115. Uno, I. (2003) Regional chemical weather forecasting system CFORS: Model descriptions and analysis of surface observations at Japanese island stations during the ACE-Asia experiment. Journal of Geophysical Research 108: 8668. Uno, I., and Coauthors (2006) Dust model intercomparison (DMIP) study over Asia: Overview. Journal of Geophysical Research 111: D12213. Volkov, K. N. (2004) Influence of Turbulence on the Deposition of Particles from a Gas-Dispersed Flow on the Wall. Journal of Engineering Physics and Thermophysics 77: 894-903. Walcek, C. J., and G. R. Taylor (1986) A theoretical method for computing vertical distributions of acidity and sulfate production within cumulus clouds. Journal of the Atmospheric Sciences 43: 339-355. Walter, B., C. Gromke, and
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/5938