WIND INDUCED DRIFT OF METALLIC CONTENT OF CONTINENTAL CRUST EXTERIOR

LIST OF FIGURES

1.1:      Illustration showing urban primary and secondary aerosol and sources         4

1.2:      Fluctuations in the mean concentration of dust content measured by

            means of an impactor                                                                                      7

1.3:      Abia State map                                                                                               9

1.4:      Schematic of the life cycle of atmospheric particles and their interactions

            with the gas and aqueous phases                                                                    12

1.5:      Wind formation                                                                                              13

1.6:      Schematic of the different modes of aeolian transport                                  17

1.7a:    Frictional Drag                                                                                                20

1.7b:    Pressure Drag                                                                                                  20

1.8:      A typical variation in measured deposition rate with particle relaxation

            time in fully developed vertical pipe flow                                                      22

2.1:      Illustration of the three dust emission mechanisms                                        28

4.1:      Plot of PS - 4 (60cm) analysis in Umudike table                                            60

4.2:      Plot of PS - 5 (60cm) analysis in Umudike table                                            61

4.3:      Plot of PS - 6 (60cm) Analysis in Umudike table                                           62

4.4:      Plot of ACB - 6 (100cm) analysis in Umudike table                                      63

4.5:      Plot of ACB - 4 (100cm) analysis in Umudike table                                      64

4.6:      Plot of PS - 1 (30cm) analysis in Umudike table                                            65

4.7:      Plot of PS - 6 (30cm) analysis in Umudike table                                            66

4.8:      Plot of ACB - 12 (100cm) analysis in Umudike table                                    67

4.9:      Plot of ACB - 11 (100cm) analysis in Umudike table                                    68

4.10:    Plot of ACB - 2 (100cm) analysis in Umudike table                                      69

4.11:    Plot of ACB - 1 (100cm) analysis in Umudike table                                      70

4.12:    Plot of PS - 2 (60cm) analysis in Umudike table                                            71

4.13:    Plot of PS - 3 (60cm) Analysis in Umudike table                                           72

4.14:    Plot of ACB - 5 (100cm) analysis in Umudike table                                      73

4.15:    Plot of ACB - 3 (100cm) Analysis in Umudike table                                     74

4.16:    Plot of PS - 6 (60cm) Analysis in Umudike table                                           75

4.17:    Plot of PS - 3 (30cm) analysis in Umudike table                                            76

4.18:    Plot of PS - 5 (30cm) analysis in Umudike table                                            77

4.19:    Plot of PS - 4 (30cm) Analysis in Umudike table                                           78

4.20:    Plot of PS - 2 (30cm) Analysis in Umudike table                                           79

4.21:    Plot of ACB - 8 (100cm) Analysis in Umudike table                                     80

4.22:    Plot of ACB - 7 (100cm) analysis in Umudike table                                      81

4.23:    Plot of ACB - 10 (100cm) Analysis in Umudike table                                   82

4.24:    Plot of ACB - 9 (100cm) analysis in Umudike table                                      83

4.25:    Plot of PS - 4 (60cm) analysis in Town table                                                  84

4.26:    Plot of PS - 5 (60cm) analysis in Town table                                                  85

4.27:    Plot of PS - 1(60cm) analysis in Town table                                                   86

4.28:    Plot of ACB - 6(100cm) analysis in Town table                                             87

4.29:    Plot of ACB - 4(100cm) analysis in Town table                                             88

4.30:    Plot of PS - 1(30cm) analysis in Town table                                                   89

4.31:    Plot of PS – 6 (30cm) analysis in Town table                                                 90

4.32:    Plot of ACB – 12 (100cm) analysis in Town table                                         91

4.33:    Plot of ACB – 11 (100cm) analysis in Town table                                         92

4.34:    Plot of ACB – 2 (100cm) analysis in Town table                                           93

4.35:    Plot of ACB – 1 (100cm) analysis in Town table                                           94

4.36:    Plot of PS – 2 (60cm) analysis in Town table                                                 95

4.37:    Plot of PS – 3 (60cm) analysis in Town table                                                 96

4.38:    Plot of ACB – 5 (100cm) analysis in Town table                                           97

4.39:    Plot of ACB – 3 (100cm) analysis in Town table                                           98

4.40:    Plot of PS – 6 (60cm) analysis in Town table                                                 99

4.41:    Plot of PS – 3 (30cm) analysis in Town table                                                 100

4.42:    Plot of PS – 5 (30cm) analysis in Town table                                                 101

4.43:    Plot of PS – 4 (30cm) analysis in Town table                                                 102

4.44:    Plot of PS – 2 (30cm) analysis in Town table                                                 103

4.45:    Plot of ACB – 8 (100cm) analysis in Town table                                           104

4.46:    Plot of ACB – 7 (100cm) analysis in Town table                                           105

4.47:    Plot of ACB – 10 (100cm) analysis in Town table                                         106

4.48:    Plot of ACB – 9 (100cm) analysis in Town table                                           107

4.49:    Plot of average concentration against atomic mass in Umudike                    108

4.50:    Plot of average concentration against atomic mass in Town                          109

4.51:    Graph of wind speed (m/s)against time (hrs) from 6:30am to 18:50pm

            on 23/12/2017                                                                                                 110

4.52:    Graph of wind speed (m/s) against time(hrs) from 3:20am to 16:00pm

            on 01/01/2018                                                                                                 111

4.53:    Graph of wind speed (m/s) against time (hrs) from 0:00am to 23:55pm

            on 07/01/2018                                                                                                 112

4.54:    Graph of wind speed (m/s) against time (hrs)  from 0:00am to 23:55pm

            on 21/12/2018                                                                                                 113

4.55:    Graph of wind speed (m/s) against time (hrs) from 0:00am to 23:55pm

On 01/01/2019.                                                                                               114

4.56:    Graph of wind speed (m/s) against time (hrs)  from 0:00am to 23:55pm

            on 06/01/2019                                                                                                 115

4.57:     Graph of Log v against Log t from Fig 4.51                                                 116

4.58:     Graph of Log v  against Log t  from Fig 4.52                                               117

4. 59:     Graph of Log v against Log t  from Fig. 4.53                                              118

4.60:     Graph of Log v  against Log t  from Fig 4.54                                               119

CHAPTER 1

INTRODUCTION

1.1                   BACKGROUND OF STUDY

Every year, the deserts in West Africa (the Sahara desert) produce a large amount of mineral dust particles that become entrained in the atmosphere. These particles are known to be important atmospheric constituents because dust particles influence the global climate by scattering and absorbing solar radiation, and absorbing and emitting outgoing long wave radiation (Tegen, 2003; Huang et al., 2006; Slingo et al., 2006). They can also cause changes in cloud properties, such as the number concentration and size of cloud droplets, which can alter both cloud albedo and cloud lifetime (Twomey et al., 1984; Huang et al., 2006).

Aerosols are small solid or liquid particles that suspend in air. While large size particles can rapidly settle out, smaller particles (< micron) have longer atmospheric lifetimes, on the order of up to weeks to months. Thus, these small particles affect climate, air quality, and human health. In urban environments, aerosols vary in composition and size, and are commonly in higher atmospheric concentrations compared to rural environments.

 The composition depends on the proximity to the source location, meteorological conditions, and types of emissions. There are roughly two types of urban aerosols. As illustrated in Figure 1, primary aerosols are directly emitted from natural or anthropogenic sources. In urban environments, primary aerosols are produced from incomplete burning of fossil fuels and wind driven, industrial or traffic-related suspension of road materials where road dust and black carbon soot are the most common. Secondary organic aerosols (SOA) are formed from gas to particle conversion (nucleation), condensation of low volatility species on pre-existing aerosols, and heterogeneous reactions of aerosols. The most distinctive feature of urban aerosols, primary and secondary, is the complexity in their chemical composition. Another important feature is that these aerosols contain a high mass fraction (10-90%) of organic compounds. In addition to chemical composition, aerosol size also controls the rate of diffusion, coagulation, settling, and other key properties such as how aerosols interact with radiation, form clouds, and penetrate into biological tissue such as in the lung lining. Primary aerosols are usually in the accumulation mode (>100 nm). Nucleation produces new aerosols in the size ranges smaller than 10 nm (nuclei mode), but these newly formed aerosols can grow larger by condensation and coagulation processes. Aitken mode aerosols include particles in the size range between 10 and 100 nm. Therefore, whereas primary aerosols can directly contribute to atmospheric aerosol mass concentrations, secondary aerosols can control both mass and number concentrations.

Coagulation takes place between different sizes of aerosols. For large aerosols, wet and dry deposition (settling) is the sink process, whereas for small aerosols, coagulation is the major sink. An important climate effect is that aerosols can act as cloud condensation nuclei (CCN; larger than 50-60 nm) and can then contribute to cloud formation. In addition to outdoor urban sources of aerosol, indoor sources are also of concern where indoor air quality is an important contributor to human health. Both indoor and outdoor aerosols have been shown to have a strong correlation with pulmonary and cardiovascular diseases. Although indoor particle concentrations can be similar to those in the outdoor environment, building filtration differences can result in significant variation in the relative compositional concentrations indoors. Indoor combustion processes such as smoking, cooking activities, and burning food are significant sources of indoor particles as are particles generated from cleaning activities and climate control systems. In addition to the home, the contribution of ultrafine particles from the workplace, especially from within offices, is also significant. Research in atmospheric chemistry has come a long way since the 1948 Donora, Pennsylvania and the 1952 London Smog events. During the cold war of the 1950s, aerosol size distributions were measured by the Soviet Union as an intelligence strategy. Plumes provided signatures for the type of aircraft from characterizing aircraft emissions. However, understanding the composition of the emitted aerosols was more elusive, and there was a limited understanding of its importance. It was not until years later that sampling of aerosols became standard protocol. In the mid-1950s, the U.S. Congress recognized and addressed air pollution with legislation, and about a decade later, the Clean Air Act of 1963 was enacted with many subsequent revisions. Yet it was not until the late 1990s that the U.S. EPA recognized the potential health risk of fine aerosols, that is PM2.5 (particulate matter <2.5 μm). Thus, the U.S. EPA’s records only show PM2.5 measurement data since year 2000, although PM10 (particulate matter <10 μm) measurements go back further in time. Aerosol mass measurements of PM2.5 have not been sufficient to provide information to understand the complex urban aerosol source, chemical and physical processes, and their impact on climate, air quality, and human health. Recently, there has been great interest in developing technologies that allow one to measure aerosol chemical composition, sizes, aerosol mixing status, aging, and multiphase reactions as a function of location and time.

Fig. 1.1: Illustration showing urban primary and secondary aerosol and sources including industrial stacks, home (e.g., wood burning), recreational (e.g., barbeque), urban emissions (e.g., asphalt), and transportation related (e.g., road and vehicle emissions) related.( Shan-Hu Lee, and Heather C. Allen, 2012).

Dust aerosol direct radiative effects are thought to be important in modulating global and regional climate. Recent studies over West Africa and based on climate models suggest significant effects of dust on the West African monsoon (WAM) development and Sahelian precipitation (Yoshioka et al., 2007; Konare´ et al., 2008; Miller et al., 2004; Lau and Kim, 2006). One remarkable fact emerging from these studies is that no clear definitive consensus has been reached on whether the atmospheric feedbacks associated with the presence of dust are more likely to increase or decrease precipitation over the Sahelian region. One of the main reasons for such contrasting arguments lies in the difficulty to accurately represent regional radiative forcing associated to dust aerosol (Balkanski et al., 2007).

This forcing occurs at the surface and within the atmosphere and can trigger some differential warming/cooling effects and thus contrasting climatic responses. Dust radiative forcing occurs in the short wave (SW or solar) and long wave (LW or thermal) spectral regions and depends on the surface albedo, the presence of clouds and the dust spatial distribution and optical properties (Liao and Seinfeld, 1998).  Dust optical properties depend on particle size distribution, particle shape and absorbing/scattering properties (refractive index). Different measurements show that these factors are extremely variable and hence very difficult to represent in climate models (Balkanski et al., 2007). Published dust particle single scattering albedo (SSA) values used to characterize the diffusive or absorbing nature of dust, are highly variable.

In situ measurements (Osborne et al., 2008; Dubovik et al., 2002; McConnell et al., 2008; Tegen et al., 2006) report high values of Saharan dust accumulation mode SSA, ranging from 0.95 to 0.99 (at _500 nm). From satellite measurements, Tanre´ et al. (2001) estimate Sahara bulk dust SSA around 0.97 ± 0.02 (at 550 nm). These latter estimates contrast with lower bulk SSA values reported in the range 0.75–0.95 (at _500 nm) (Otto et al., 2007; Raut and Chazette, 2008; Haywood et al., 2001). The dust source mineralogy (iron oxide content), dust coating by absorbing aerosol (e.g., biomass burning), size distribution of particles and measurement techniques are all factors that contribute to the variability of observations. For example, McConnell et al. (2008) showed that the addition of the coarse mode in dust SSA retrieval induced a significant change from 0.98 to 0.90 (at 550 nm).

 Many studies have detailed the impact of dust absorption properties on radiative forcing (Balkanski et al., 2007; Wang et al., 2006; Li et al., 2004). Fewer have however focused on the characterization of possible climate responses to this variability, especially concerning regional scale precipitation (Rodwell and Jung, 2008; Miller et al., 2004).

Innumerable sources generate aerosols non-uniformly in time and distribute them non-uniformly at various points on the earth's surface. Carried by the wind, these aerosols are stirred by atmospheric turbulence. Temporary concentration fluctuations caused by shifting winds have been recorded. In addition, molecular diffusion intensively and significantly levels out the concentration of aerosols in admixtures of water vapor and gas found in atmospheric air. Particles of different sizes continuously undergo segregation in aerosols. In this manner, zones with different concentrations are crested in the atmosphere. All aerosol parameters, including concentration in the atmosphere, fluctuate strongly in time and space. Fig.1.2. illustrates this phenomenon by showing data describing numerical concentration of dust in a factory shop obtained by means of an impactor (Fuchs, 1986). Air samples 5cm³ in volume was taken every minute with a sampling time near 0.1s. The scale of fluctuations was comparable to mean concentration. These "small-scale" fluctuations are caused by a number of random processes.

The connection between temporal and spatial fluctuations of aerosol concentration is of great interest. For small-scale fluctuations of wind velocity, temperature and moisture content or "frozen turbulence" (Fuchs, 1986) is observed in the atmosphere. Spatial fluctuations in wind direction during short time intervals are repeated as temporal fluctuations. According to general statistical laws, fluctuations of mean aerosol concentration decrease with increasing averaged time and averaged volume. Here the following phenomenon begins to take effect: as the scale of fluctuations increases, they gradually lose their random nature and become more and more regular.

Fig. 1.2: Fluctuations in the mean concentration of dust content measured by means of an impactor (Fuchs, 1986).

The wind-driven emission, transport, and deposition of sand and dust by wind are termed aeolian processes, after the Greek god Aeolus, the keeper of the winds. Aeolian processes occur wherever there is a supply of granular material and atmospheric winds of sufficient strength to move them. On Earth, this occurs mainly in deserts, on beaches, and in other sparsely vegetated areas, such as dry lake beds. The blowing of sand and dust in these regions helps shape the surface through the formation of sand dunes and ripples, the erosion of rocks, and the creation and transport of soil particles. Moreover, airborne dust particles can be transported thousands of kilometers from their source region, thereby affecting weather and climate, ecosystem productivity, the hydrological cycle, and various other components of the Earth system (Greeley and Iversen 1985).

The terms dust and sand usually refer to solid inorganic particles that are derived from the weathering of rocks. In the geological sciences, sand is defined as mineral (i.e., rock-derived) particles with diameters between 62.5 and 2,000 µm, whereas dust is defined as particles with diameters smaller than 62.5µm. In the atmospheric sciences, dust is usually defined as the material that can be readily suspended by wind (Shao, 2008), whereas sand is rarely suspended and can thus form sand dunes and ripples, which are collectively termed bedforms.

1.2       STATEMENT OF PROBLEM

Dust aerosols have always been seen as environmental pollution as it travels from one place to another. Hence, the metallic analysis and physical properties of aerosols are deemed necessary for this research.

1.3       AIM OF THE STUDY

The aim of this research work is to analyse  and compare dust aerosol in Umudike (Ikwuano LGA) and Ubakala ( Umuahia North LGA) of Abia state; South – Eastern Nigeria.

1.4       OBJECTIVES OF THE STUDY

•      To construct suitable collectors for aerosols.

•      To collect a measurable quantity of aerosols over a period of two years.

•      To carry out elemental analysis of aerosols collected.

•        To estimate the wind speed in the vicinity of the study area.

•       To determine the average speed with which the entrained particles hit the ground.

•       To determine the average time taken for the entrained particles to hit the ground.

•      To determine average distance travelled by entrained particles before hitting the ground.

1.5       THE AREA OF STUDY

The location, position and size of the study area is bounded by latitude 05º29'N, longitude 07º33'E, altitude 122m above sea level.

Fig. 1.3:  Abia State map (Culled from http://www.citypopulation.de/php/nigeria-admin.php?adm1id=NGA001).

 Abia State, which occupies about 5,834 square kilometres, is bounded on the north and northeast by the states of Anambra, Enugu, and Ebonyi. To the west of Abia is Imo State, to the east and southeast are Cross River State and Akwa Ibom State, and to the south is Rivers State. The southern part of the State lies within the riverine part of Nigeria. It is low-lying tropical rain forest with some oil-palm brush (Hoiberg, 2010). The southern portion gets heavy rainfall of about 2,400 millimetres (94 in) per year especially intense between the months of April through October. The rest of the State is moderately high plain and wooded savanna. (Hoiberg, 2010).  The most important rivers in Abia State are the Imo and Aba Rivers which flow into the Atlantic Ocean through Akwa Ibom State.

1.6       THE LIFE OF AN ATMOSPHERIC PARTICLE

Atmospheric particles originate either as primary particles - by direct emission from a source or as secondary particles - through in-situ formation from the gas phase (nucleation). Particles vary in size from a few nanometers to tens of micrometers, with their composition reflecting their source. Secondary particles can be created in different parts of the atmosphere, sometimes high near a cloud or even the top of the troposphere and sometimes near the surface of the earth. After entering the lower atmosphere, new particles can exist for several days depending on removal processes. During their lifetime, they are changed by processes such as dilution, dispersion, coagulation, and chemical reaction.

Upon their emission to (or formation in) the atmosphere, particles move under the influence of local air currents, simultaneously diffusing and, possibly, colliding through turbulent and Brownian processes. These processes dilute the particles and mix them with other particles and gaseous compounds (Figure 1.4). Collisions between two or more particles typically result in coagulation, wherein the original particles adhere to form larger particles having the sum of the original masses. Coagulation effectively increases the mass of particles while depleting smaller particles, and often is an important mechanism for shifting the aerosol-size spectrum toward larger particle sizes. If the particles avoid coagulation, which is relatively rapid near their source, they travel beyond the source region, interacting with vapors such as H₂SO₄, organics, HNO₃, and NH₃. These semivolatile or reactive vapors, when their concentration exceeds specific thresholds, condense upon available surfaces, including the surfaces of existing particles. Some condensed vapors react with other vapors and attract them to the condensed phase as well. H₂SO₄ reacts with NH₃, for example, and condensed organic compounds can dissolve other organic vapors. Particles form also as the consequence of gas-phase reactions such as the reaction of NH₃ with HNO₃ to form NH₄NO₃, thus transferring gaseous material to the particulate phase. Consequently the particles grow in size and contain material derived both from their origin and from the places where they have been.

Some of this deposited material may return to the gas phase if the conditions are right. For instance, NH₄NO₃ can volatilize to produce NH₃ and HNO₃, and organic particles can volatilize to emit organic vapors. Because semi-volatile particle components exchange continuously between the gas and condensed phases, it is difficult to measure PM concentrations in the atmosphere and to completely determine aerosol behavior and impact.

Fig. 1.4:  Schematic of the life cycle of atmospheric particles and their interactions with the gas and aqueous phases (Seinfeld and Pandis, 1998).

1.7       ATMOSPHERIC CONDITIONS

Wind is considered to be the movement of air over the surface of the Earth from regions of high pressure to low pressure. The larger the atmospheric pressure gradient, the higher the induced wind speed which gives rise to potential storms and hurricanes that exhibits the wind’s full and often devastating forces (Tong, 2010). Atmospheric conditions and movements determine the winds speed and direction. The atmosphere is forced to move due to the rotation of the Earth and also due to the heat absorbed from the Sun through radiation. As the Earth spins on its axis it creates a circulating force more commonly known as the Coriolis Effect which pulls the atmosphere along with it. This force decreases with distance from the Earth, making wind speeds to be maximum near the Earth’s surface. The difference between air speeds causes mixing to occur between the air molecules which develops turbulence, this turbulence results in what is called wind on the Earth’s surface (Manwell et al., 2006). Heat energy absorbed from the Sun greatly influences global wind patterns. Due to the angle on which the Earth rotates, this heat energy is not evenly distributed. Tropical regions receive more solar energy than that can be radiated back to space. The amount of solar energy received at the Earth’s surface reduces as one moves closer to the poles. As the air is heated it becomes less dense and rises, which causes the cooler less dense air to be pulled down by atmospheric pressure from cooler regions. This is why hurricanes and other wind driven meteorological phenomena are more common in warm climates found in the tropical regions near the equator (Siraj, 2010).

Fig. 1.5: Wind formation (Hk-Electric, 2011)

The heated air then travels and moves by convection currents away from the warm region where it begins to cool, as the air cools it becomes denser and falls in altitude. This constant cycle of heating and cooling of air circulates warm air around the world which results in wind (Tong, 2010).

1.8       WIND MOVEMENT

The temperature differences produced by inequalities in heating cause differences in air density and pressure that propel the winds. Vertical air motions are propelled by buoyancy: a region of air that is warmer and less dense than the surroundings is buoyant and rises. Air is also forced from regions of higher pressure to regions of lower pressure. Once the air begins moving, it is deflected by the Coriolis force, which results from Earth’s rotation. The Coriolis force deflects the wind and all moving objects toward their right in the Northern Hemisphere and toward their left in the Southern Hemisphere. It is so gentle that it has little effect on small-scale winds that last less than a few hours, but it has a profound effect on winds that blow for many hours and move over large distances.

At the surface, some of the sinking air moves back toward the lower pressure at the equator. This flow of air toward the equator is known as the trade winds. Due to the Coriolis force, a force that results from the rotation of the Earth, the trade winds are deflected to the west. In the northern hemisphere, the trade winds blow from the northeast, and in the southern hemisphere, they blow from the southeast. The trade winds complete a thermally driven convection cell that begins with the Sun warming the tropics, air rising above the equator, flowing toward the poles, then sinking near 30° latitude and returning to the equator. At the equator, the trade winds from the northern hemisphere meet the trade winds from the southern hemisphere forming a boundary called the inter-tropical convergence zone (ITCZ).

The rotation of Earth also affects the movement of air. In the northern hemisphere, Earth’s rotation deflects air from left to right, while in the southern hemisphere, it deflects air from right to left. This deflection is called the Coriolis effect. As air moves toward a low-pressure center, the deflection causes the air to spiral around the center rather than travel straight into the center. The inward spiraling of air causes the formation of circular bands of thunderstorms, which are a distinctive feature of tropical storms and hurricanes, along with spiraling winds. The spiraling winds rotate faster as they approach the center. Centrifugal force flings the rotating air outward, making it increasingly difficult for air to reach the center.

1.9       MODES OF WIND-BLOWN PARTICLE TRANSPORT

The transport of particles by wind can occur in several modes, which depend predominantly on particle size and wind speed (Figure 1.6). As wind speed increases, sand particles of ~100 μm diameter are the first to be moved by fluid drag. After lifting, these particles hop along the surface in a process known as saltation (Bagnold 1941, Shao 2008), from the Latin salto, which means to leap or spring. The impact of these saltators on the soil surface can mobilize particles of a wide range of sizes. Indeed, dust particles are not normally directly lifted by wind because their inter-particle cohesive forces are large compared to aerodynamic forces. Instead, these small particles are predominantly ejected from the soil by the impacts of saltating particles (Gillette et al. 1974; Shao et al. 1993a). Following ejection, dust particles are susceptible to turbulent fluctuations and thus usually enter short-term (~ 20 - 70 µm diameter) or long-term (< ~20 µm diameter) suspension (Figure 1.6). Long-term suspended dust can remain in the atmosphere up to several weeks and can thus be transported thousands of kilometers from source regions (Gillette and Walker, 1977; Zender et al. 2003a; Miller et al., 2006). As outlined in the next section, these dust aerosols affect the Earth and Mars systems through a wide variety of interactions.

The impacts of saltating particles can also mobilize larger particles. However, the acceleration of particles with diameters in excess of ~500 μm is strongly limited by their large inertia, and these particles generally do not saltate (Shao, 2008). Instead, they usually settle back to the soil after a short hop of generally less than a centimeter, in a mode of transport known as reptation (Ungar and Haff, 1987). Alternatively, larger particles can roll or slide along the surface, driven by impacts of saltating particles and wind drag forces in a mode of transport known as creep (Bagnold, 1937). Creep and reptation can account for a substantial fraction of the total wind-blown sand flux (Bagnold, 1937, Namikas, 2003).

The transport of soil particles by wind can thus be crudely separated into several physical regimes: long-term suspension (< ~20 μm diameter), short-term suspension (~20 – 70 μm), saltation (~70 – 500 μm), and reptation and creep (> ~500 μm) (Figure 1.1). These four transport modes are not discrete: each mode morphs continuously into the next with changing wind speed, particle size, and soil size distribution. The divisions based on particle size between these regimes are thus merely approximate.

Consequently, global changes in dust deposition to ecosystems are hypothesized to have contributed to changes in CO₂ concentrations between glacial and interglacial periods (Martin 1990; Broecker and Henderson, 1998) as well as over the past century (Mahowald et al., 2010). Moreover, dust-induced changes in CO₂ concentrations may also play a role in future climate changes (Mahowald, 2011).

Fig. 1.6: Schematic of the different modes of aeolian transport

(Reprinted from Nickling and McKenna Neuman (2009), with kind permission from Springer Science+Business Media B.V.)

1.10     MOTION OF AEROSOL PARTICLE RELATIVE TO THE SURROUNDING       AIR MASS

The motion of aerosol particles in the atmosphere can be expressed in two distinct types:  uniform motion and diffusive motion. Uniform motion is probably most common to our everyday experience. It is sometimes called unidirectional motion. Here, particles move smoothly along straight paths or relatively gentle curves without abrupt changes in direction (barring occasional collisions with other massive objects). Examples are a baseball thrown from left field to home plate, or a helium balloon rising gently in calm air. Diffusive motion is much more chaotic and random in direction. In certain contexts diffusive motion is also called Brownian motion (thermally-driven random motion of a particle in a gas or liquid), Brownian diffusion, or just random-walk motion. Fill the bottom half of a box with black marbles and the top half of the box with white marbles, cover, and shake vigorously. Eventually you will end up with a relatively uniform mixture of black and white marbles. If you follow the detailed path of one of the black marbles that happens to have reached the top, you will find it did not move in a straight line. Rather, it followed a jagged path, sometimes even retreating downward, before by chance reaching the top. Or imagine an ideal frictionless billiard table where a number of balls have been set in motion. If you follow the motion of an individual ball, such as the cue ball, as it collides with other balls and bounces from the sides of the table, you will note a velocity that frequently changes in magnitude and direction. After a number of collisions, a ball started in one comer might be found in another comer; however, the total distance covered by the ball will be much larger than the straight line distance between the two comers of the table.

Aerosol particles in the earth's atmosphere experience both types of motion. To some extent, both types are simultaneously present. However, due to the wide range of aerosol particle sizes, certain types of motion tend to be more important in certain size regimes, especially if gravity is the only external force present. For example, for small aerosol particles, such as ultrafine particles (diameters less than 0.1µm), Brownian diffusion frequently predominates. For large aerosol particles, such as the larger coarse particles (diameters between 2 and 100 µm), uniform downward motion due to gravity frequently dominates. The presence of other external forces, such as the force of an electric field on a charged particle, can create uniform motion over the entire aerosol size range. In the gravity-free environment of a spacecraft, it is theoretically possible for diffusion to dominate motion over the full size range.

1.11     SEDIMENTATION DEPOSITION IN CONFINED SPACE

The simplest means of depositing aerosols is sedimentation under gravity. For this purpose, a chamber or a vessel with vertical walls and a closely fitted lid is filled with aerosol. The aerosol settles on a plate located at the bottom of the vessel. However, this method has a number of drawbacks. Complete settling of fine particles takes a long time. In addition, because of diffusion, fine particles can settle on side walls. Likewise, owing to image forces, charged particles can settle on side walls. Droplets of more or less volatile liquids may evaporate. Because the usual weight concentration of aerosols is small, the weight of the plate may prove to be greater by an order of magnitude than that of the deposit. This causes large errors due to inaccurate weighing. For this reason, this method is not used for determining weight concentration. In the sedimentation method, however, unlike the impaction method, settling particles do not rebound from the plate or get blown off or destroyed. Coagulation during sedimentation is insignificant and surface concentration of particles in the deposit is relatively uniform.

1.12     FRICTIONAL AND PRESSURE DRAG

There are two components of drag force which are frictional drag and pressure drag. Every material has its unique frictional coefficient and will oppose fluid flow to varying degrees. (Cakir, 2012). The friction coefficient of a surface effects greatly the development of a boundary layer on the surface and scales with Reynold’s number (Princeton University, 2013). Pressure drag is created by eddies which are formed as the fluid flows past an obstacle. The fluid creates a space after passing the obstacle which is commonly known as a wake and is less acceptable to Reynold’s number than that of frictional drag (Moffatt, 1963). Frictional drag is the primary concern where attached flows are analysed whereby there is no separation of the fluid stream. Pressure related drag is significant for separated flows and is related to the cross sectional area of the body (Princeton University, 2013).

Fig. 1.7a:  Frictional Drag (Warner, 2010)

Fig. 1.7b:  Pressure Drag (Warner, 2010)

1.13     GENERAL EXPERIMENTAL CHARACTERISTICS OF DEPOSITION AND      FICK’S LAW OF DIFFUSION

Usually the results of deposition experiments or calculations are presented as curves of non-dimensional deposition velocity versus non-dimensional particle relaxation time. The deposition velocity, V_dep, is the particle mass transfer rate on the wall, J_wall , normalized by the mean or bulk density of particles (mass of particles per unit volume), ρ_p,_m, in the flow:

The particle relaxation time, τ , is a measure of particle inertia and denotes the time scale with which any slip velocity between the particles and the fluid is equilibrated. As demonstrated below, τ depends, among other things, on the particle radius; hence the abscissa of the usual deposition curves represents increasing particle radius. V_dep and τ are made dimensionless with the aid of the fluid friction velocity          

where ν is the kinematic viscosity of the fluid 

 Many previous studies give experimental measurements of the deposition velocity (Friedlander and Johnstone, 1957; Liu and Agarwal, 1974; McCoy and Hanratty, 1977; Wells and Chamberlain, 1967). Although there is considerable scatter, these data illustrate the basic characteristics shown in Figure 1.8. The results fall into three distinct categories:

a)      At first, as  increases, the deposition velocity decreases. This is the so-called turbulent diffusion regime, in which a turbulent version of Fick’s law of diffusion (see pg 22, front page) applies.

b)      The striking feature of the next zone, the so-called eddy diffusion impaction regime, is that the deposition velocity increases by three to four orders of magnitude.

c)      The third regime of deposition, usually termed the particle inertia moderated regime, results in an eventual decrease in the deposition velocity for large particle sizes. The borders between the three regimes are not sharp, as one effect gradually merges into another, and depend on flow conditions.

Fig. 1.8: A typical variation in measured deposition rate with particle relaxation time in fully developed vertical pipe flow (Regime 1, turbulent diffusion; regime 2, turbulent diffusion-eddy impaction; regime 3, particle inertia moderated).

1.14     MOLECULAR AND TURBULENT DIFFUSION

Most mass-transfer textbooks (e.g., Kay and Nedderman, 1988) show that one can calculate the flux of small particles in a turbulent boundary layer by integrating a modified Fick’s law of diffusion,

where D_B is the Brownian diffusivity; D_t is the turbulent diffusivity, which varies with position; y is the perpendicular distance from the wall; and     is the gradient of particle partial density (same as concentration gradient). D_B is given by the Einstein equation incorporating Cunningham’s (1910) correction (C_C = 1 + 2.7Kn) for rarefied gas effects,

where k is the Boltzmann constant, T is the absolute temperature, and Kn is the Knudsen number defined by Kn = l/2r, where l is the mean free path of the surrounding gas and r is the radius of a particle. Another semiempirical form for the Cunningham factor,

 C_C = 1 + Kn[a + b exp(−c/Kn)], is also widely used:

Davies (1945) gave the values of the constants as a = 2.514, b = 0.8, and c = 0.55. Slightly different values for these constants are sometimes used in the literature. Equ. 1.3 shows that D_B decreases with increasing r. Equ. 1.2 therefore predicts that the mass flux of particles and deposition velocity decrease continuously with increasing particle size.

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