Effect of attachment configuration on the trapping

Environ Earth Sci (2010) 61:1375–1384 DOI 10.1007/s12665-010-0455-0

ORIGINAL ARTICLE

Effect of attachment configuration on the trapping efficiency of Vaseline-coated slide catchers for windblown particles Mustafa Basaran • Gunay Erpul • A. Ugur Ozcan • Pieter Bogman • Wim M. Cornelis • Donald Gabriels

Received: 27 March 2009 / Accepted: 6 January 2010 / Published online: 3 February 2010  Springer-Verlag 2010

Abstract There are various types of the windblown sediment traps developed for wind tunnel and field studies. One of the main supports expected from these traps is in measuring surface dust concentrations to appropriately derive flux equations. The measurement performance and accuracy of a trap is very important and depends strictly upon the physical characteristics and the behaviors of dust grains with air flows. This paper presents the measurement results of static pressure distribution (SPD) of wind flow around Vaseline-coated slide (VCS) catchers with an aim of finding out whether or not particle trapping efficiency (g) of the VCS is related to the SPD. The SPD was evaluated by a wind reduction coefficient (Rc) in a series of wind tunnel experiments with different VCS settings which have different attachment configurations on a pole. Three VCS configurations were considered: a configuration on a circular plastic pole (CPP) and two configurations on wooden square poles (WSP1 and WSP2, respectively). Thus, the primary contribution of this work was to experimentally analyze the effect

M. Basaran (&) Department of Soil Science, Seyrani Faculty of Agriculture, Erciyes University, Kayseri, Turkey e-mail: [email protected]; [email protected] G. Erpul Department of Soil Science, Faculty of Agriculture, Ankara University, Dıskapı, Ankara, Turkey

of the different attachment configurations on the SPD, and the secondary objective was to determine the effect of the SPD on the g. It was shown that spatial correlation and spatial pattern of the Rc were different in the surrounding area of each configuration, and ANOVA and DUNCAN tests indicated that g(s) of WSP1, WSP2, and CPP were different at the significant level of P B 0.05 with the mean of 0.94 ± 0.09, 0.63 ± 0.14, and 1.13 ± 0.07, respectively. Additionally, the amount of PM20, PM40, PM60, PM80, and PM100 trapped by the configurations of WSP1, WSP2, and CPP considerably varied depending upon the particular aerodynamic circumstances associated with every configuration. Keywords Vaseline-coated slide  Wind erosion  Wind tunnel  Sediment traps  Trap efficiency Abbreviations SPD Static pressure distribution Rc Wind reduction coefficient g Catch efficiency VCS Vaseline-coated slide CPP Circular plastic pole arrangement of a VCS with a horizontal frame on a pole WSP1 Wooden square pole arrangement of a VCS with pushpins on a pole WSP2 Wooden square pole arrangement of a VCS with a vertical frame on a pole PM Particulate matter

P. Bogman  W. M. Cornelis  D. Gabriels Department of Soil Management and Soil Care, Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium

Introduction

A. Ugur Ozcan Department of Forest Engineering, Faculty of Forestry, Karatekin University, C¸ankırı, Turkey

Model studies for dust emission, transport, and deposition processes might be essential when dealing with

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environmental and health problems caused by airborne particles. For example, the deposition of atmospheric dust was recognized as an important environmental process worldwide (Goossens and Riksen 2004), and also, the emission of soil particles by wind is considered as a major contemporary environmental problem (Niemeyer et al. 1999). Chandler et al. (2002) reported that the determination of the release rates of aerosol-size particulates from disturbed soils during wind erosion events is a significant step required to incorporate the air quality prediction into wind erosion models. Although sources of suspended dust are numerous and varied, similar processes occur when dust is emitted from deserts, dry lake beds, agricultural fields, dirt roads, construction sites, and other areas where the surface is bare and erodible particles are exposed to forces of winds (Zobeck and Van Pelt 2006). Finer dust particles emit from the soil surface when it is abraded by saltating aggregates and mineral grains, through entrainment from the soil surface due to the turbulent eddies in surface winds or from agricultural operations (Gillette and Walker 1977; Kind 1992; Shao et al. 1993; Loosmore and Hunt 2000; Shao 2000). Zobeck and Van Pelt (2006) stated that the particles moved by wind can range up to about 1 mm in diameter, but the particles traveling over great distances are usually much smaller than 100 lm. Accurate and reliable methods of measuring windblown sediments are necessary for confirming and calibrating the theoretically derived flux equations, measuring sediment loss in a field, and determining the related damage and source of pollutants (Nickling and Neuman 1997; Zobeck et al. 2003). Achieving this, on the other hand, needs a proficiency in sampling of the windblown soil particles. There are several sediment traps for field use, those of which developed by Bagnold (1954), Leatherman (1978), De Ploey (1980), Wilson and Cooke (1980), and Fryrear (1986) are very well-known. Collectors range from the open pits or trench traps dug in sand (Jackson 1996) to the vertical cylindrical traps oriented into the flow (Leatherman 1978). Gillette and Walker (1977) reported that active samplers were often used to trap the suspended dust particles smaller than 20 lm and those up to 60 lm (Bagnold 1941). Unlike the sampling traps that directly collect transported material, Spaan and van den Abeele (1991) used an indirect method by which a microphone was able to estimate the number of sand-sized windblown particles in transport, and they called it a saltiphone. Nickling and Neuman (1997) sub-divided traps into two broad groups: the first one with horizontal sampling orifices and the other with vertical sampling orifices. Besides, Zobeck (2002) made a distinction between passive and active sampling processes such that the former depended on wind conditions during sample collection

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and the latter relied on some type of suction provided by a vacuum pump to draw a known volume of air and particles into traps. The review of Visser et al. (2004) gives a vital significance of the direct measurement techniques in a field. By these techniques, particles are caught by a catcher during a windstorm. On the other hand, although related to the type, the efficiency of a sediment trap is the most important characteristic of it, and a research on the efficiency of a trap is significant since it shows how well a sampler collects sediment compared to the actual amount of sediment in the wind stream. Therefore, the sampling efficiency of a sampler must be known if estimates of true sediment transport are needed (Zobeck et al. 2003). Numerous studies were conducted in wind tunnels and under field conditions to determine sampling efficiencies of various catchers (Bagnold 1954; Gillette and Walker 1977; Leatherman 1978; De Ploey 1980; Wilson and Cooke 1980; Fryrear 1986; Jackson 1996; Goossens et al. 2000; Goossens and Offer 2000; Cornelis and Gabriels 2003). Drew and Lippmann (1978) emphasized that it was not necessary for sediment traps to have a 100% efficiency, and sediment traps might also be useful even if they have a low efficiency as long as it is known. Most sediment traps have a range of efficiencies changing with wind speed and particle diameter or aggregate size. In sediment trapping, generally, it is more difficult to catch the particles that move by suspension than the particles that move by saltation because finer suspended particles are easy to be carried by a wind stream and may not enter into traps if it is not iso-kinetic, and they are not easily trapped by a screen or other physical barrier as well (Zobeck et al. 2003). Goossens and Offer (2000) determined efficiencies of the Big Spring Number Eight (BSNE, Fryrear 1986) and the Modified Wilson and Cooke (MWAC) traps at low wind velocities (1–5 ms-1) using a silty loess that consisted of 95% silt (2–63 lm), and results showed that the efficiencies of both BSNE and MWAC traps were 40 and 80%, respectively. Nickling and Neuman (1997) used a wedgeshaped sediment trap which created a venturi effect that enabled air and sediment to be easily drawn into the sampler, thereby improving the sampling efficiency. Previous studies emphasized a static pressure effect at the trap inlet of a catcher. For instance, Fryrear (1986), Shao et al. (1993), Goossens et al. (2000), and Cornelis and Gabriels (2003) reported that the trap efficiency of the samplers with an inlet declined with increasing wind velocity. According to Nickling and Neuman (1997) and Goossens et al. (2000), this could be due to an increasing stagnation pressure at the trap inlet, which hindered the sediment from entering the trap. Obviously, the efficiency of a trap in wind erosion measurements is an important parameter, and in many

cases suspension trap efficiencies at high wind velocities are still unknown. The present study is about the efficiency and iso-kinetic characteristics of Vaseline-coated slides (VCS). A VCS, having no orifice or inlet, can be grouped in the passive sediment traps. They can be more easily prepared and are much cheaper than the others. However, only a few detailed studies were performed on the efficiency of the VCS. In determining the efficiencies of the VCS and the MWAC sediment traps by wind tunnel experiments using different soil textures at different wind velocities, Youssef et al. (2008) indicated that the efficiency depended critically on particle size and wind speed. This study aimed at a better understanding of the aerodynamic behavior of three different VCS catcher attachment configurations and how this relates to the catcher efficiency.

Materials and methods Experimental setup The experiments were carried out in the wind tunnel of the International Center for Eremology (ICE), Ghent University, Belgium. The wind tunnel is a closed blowing-type tunnel with a 12-m long, 1.2-m wide, and 3.2-m high working section. Gabriels et al. (1997) and Cornelis et al. (2004) give a detailed description of the ICE wind tunnel together with the results of a series of tests to specify the various parameters of wind, such as vertical and transversal wind-velocity distribution and wind direction. Wind speed profiles in the tunnel are characterized by the Prandtl–von Ka´rma´n logarithmic equation (Eq. 1): u z uðzÞ ¼ ln for z \ z0 ð1Þ k z0 where u(z) is the wind speed at height z, z0 the aerodynamic roughness height, u* the wind shear velocity, and k the von Ka´rma´n’s constant. The study was conducted at a single reference wind speed of 11 m s-1. This reference wind speed was measured with a 16-mm vane probe (Testo, Lenzkirch, Germany), which was located at x = 1.2 m, y = 0.6 m, and z = 1.0 m in the tunnel. Around a VCS catcher, wind speed was recorded using three ball sensors having 4 mm outside diameter and Ni thermocouple (Testo, Lenzkirch, Germany). Because of small differences in the measured wind speeds among the ball sensors, all recorded values were corrected with respect to the reference probe (Fig. 1). Since wind speed was adjusted by blades in the ICE wind tunnel, and obtaining exactly the same reference wind speed during different experiments was hardly possible, a second correction was introduced by Eq. 2:

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Wind velocity with ball probe (m/sn)

Environ Earth Sci (2010) 61:1375–1384 12 1. probe 2. probe

11

3. probe

10 9 y = 0,8897x + 5,486 2 R = 0,9897 y = 0,8869x + 5,376 2 R = 0,9924

8 7 6

y = 0,9065x + 5,586 2 R = 0,9965

5 6

7

8

9

10

11

Referans wind velocity (m/sn)

Fig. 1 Linear regressions between the reference vane probe and the ball probes

ui;c ¼ ui;m

uref uref;m

ð2Þ

where ui,c is the corrected wind speed at location i (m s-1), uref,m is the wind speed measured simultaneously with ui,m using the reference probe (m s-1), and uref is the mean of N measured reference wind speeds, and N the number of series. Basically, a VCS catcher consists of a transparent glass slide (26 9 76 mm) rubbed with Vaseline, which is fixed on a pole and oriented toward a potential source of windblown particles. Figure 2 shows a side view of the experimental setup with a pole holding the VCSs at three different heights in the wind tunnel. In each run, the VCSs were placed on the pole at three heights of 20, 40, and 80 cm. The poles were located vertically to the prevailing wind direction at x = 9.4 m horizontal distance from the entrance of the tunnel test section. The most important factor that affects the efficiency of a VCS is the reduction in wind speed at its windward side. In other words, wind pressure on its windward side leads to the wind speed reduction that could influence the VCS’s catching efficiency of windblown particles. Not only a pole shape but also different VCS attachment configurations to a pole might be considered as significant factors in reducing wind speed and its spatial variation around a pole. Hence, three different VCS catcher attachment configurations were selected for studying the interaction between wind speed reduction and catcher’s efficiency. Figure 3 shows the poles with different VCS arrangements. The pole in Fig. 3a was a plastic with a circular cross section of 4 cm in diameter, while the poles in Fig. 3b and c were wooden square poles with an identical cross-sectional squared area of 4.5 cm 9 4.5 cm. The attachments of a VCS to each type of the pole were also different: (1) a VCS is attached to the plastic circular pole

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Fig. 2 Side view of the experimental setup with a pole holding three VCSs at different heights in the wind tunnel

Fig. 3 Front view of the poles and the positioning of VCSs with three different configurations, a CPP, b WSP1, and c WSP2

by means of two horizontal pieces of wood (1.0 9 1.5 9 3.5 cm) (Fig. 3a) (CPP), (2) a VCS is fastened to the wooden square pole by pushpins at three points (Fig. 3b) (WSP1), (3) a VCS is attached to the wooden square pole by means of two vertical pieces of wood (1.0 9 1.5 9 5.5 cm) and a pushpin further supported the VCS from bottom (WSP2) (Fig. 3c). The wooden pieces by which a VCS is fixed on a pole in the configurations of the CPP and the WSP1 were glued to poles beforehand. Geostatistical mapping of reduction coefficient A surrounding area of 20.5 9 20.5 cm was chosen to determine the spatial variation of ‘‘reduction coefficient’’ (Rc) of the wind speed around the poles placed in the center of this area. The Rc was defined by Cornelis and Gabriels (2003) (Eq. 3): Rc ¼ 1 

u uw

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ð3Þ

where u is the arithmetic mean of the wind speed measurements in the presence of a pole, and uw is the arithmetic mean of the wind speed measurements in the absence of a pole. A top view of the experimental design for the geostatistical mapping of the Rc is given in Fig. 4. For each pole type, with a reference wind speed of 11 m s-1, wind speeds were measured with three ball probes at 40 points in the given area at the VCS heights of 20, 40, and 80 cm. Another set of measurements was performed without a pole in the same points, area and heights as those of the experiments with a pole. In this way, a total of 480 wind speed measurements were obtained. The horizontal spatial variability and the spatial pattern of the Rc in the surrounding area of poles were determined by geostatistical methods for each height. The basic theory of the geostatistics, first presented by Matheron (1965), was well established by Journel and Huijbregts (1978). The experimental semi-variogram for the separation distance, (lag) h, was calculated by Eq. 4:

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Fig. 4 Top view of the experimental setup for determining the spatial distribution of the Rc (dots show measurement location)

1 X ½zðxi Þ  zðxi þ hÞ2 2NðhÞ i¼1 NðhÞ

c  ðhÞ ¼

ð4Þ

where z(xi) is a Rc value at the spatial location xi, and N(h) the number of pairs with the separate distance (lag) h. The spherical and Gaussian models were fitted to the experimental semi-variograms. The empirical semi-variograms were directionally calculated at the angles of 0 (N–S), 45 (NE–SW), 90 (E–W), and 135 (SE–NW) for the Rc. This directional examination of the variogram surfaces indicated no severe anisotropy, and therefore, only omni-directional variograms were obtained selecting a best-fit model by the least squares regression method and modeled with the isotropic functions to determine spatially dependent variance within the surrounding area of the poles for each height. The values at the observation points were used for predicting values at unknown points by the ordinary block kriging interpolation method by models and parameters of the generated semi-variograms. The software package GS ?7 (Gamma Design Software) was used to perform geostatistical computations. Determination of the efficiency of VCS catchers Unlike the Rc determinations performed at three heights, for measuring the efficiency of the catchers in each configuration, VCSs were placed at the heights of 5, 20, 40, 60, 80, and 120 cm. As detailed previously, three configurations were considered: one configuration representing a VCS setup on a circular plastic pole (CPP) and

two configurations representing VCS setups on wooden square poles (WSP1 and WSP2, respectively). The WSP1 is differentiated from the WSP2 by the geometry of the attachment of a VCS to the pole (Fig. 3). A sandy loam (Soil Survey Staff 1999) was used after air-dried then ground and sieved (2.0 mm). The soil contained 245 g kg-1 sand, 651 g kg-1 silt, and 104 g kg-1 clay, and organic matter and CaCO3 contents of the soil were 20 and 4 g kg-1, respectively. As much as 10 g of soil of 1 cm 9 35 cm (soil strip) was laid evenly on a commercial emery paper at the windward horizontal distance of 3 m from a set pole (Fig. 5). After each run by the reference wind speed of 11 m s-1 (free stream wind speed), total windblown sediments from the commercial emery paper was determined by weighing the remaining soil on the paper. These experiments were replicated seven times to assess the VCS efficiency for a particular pole configuration. The sediment amount trapped by each VCS was determined by counting the number (#) of particles per slide located at the six heights (5, 20, 40, 60, 80, and 120 cm). The soil particles caught by a VCS were classified as five different size classes (0–20, 20–40, 40–60, 60–80, and 80– 100 lm) with a Leitz polarizing microscope (Laborlux 11 Pol, Nu¨rberg, Germany) and the mass of particles per slide was calculated as: n X m X 1 q¼q 1012 Xij Vj ð5Þ nA T i¼1 j¼1 where q is the mass flux of sediment per slide (mg m-2 s-1), q the particle density (kg m-3), A the area covered by the microscope lens (2.545 9 10-6 m2), T the duration of the experiment (1 s), n the number of analyzed fields per slide (five in our study), m the number of diameter classes (five in our study), Xij the number of particles in diameter class j (=1, 2,…, m) in field i (=1, 2,…, n), and Vj the volume of particle in diameter class j (m3). The parameter Vj depends on the shape of the particles. We assumed the particles to be of spherical shape. Finally, a dimensionless efficiency (g) for every configuration was calculated as: g¼

Q Qt

ð6Þ

where Q is the integrated mass of sediment trapped by the VCSs placed at the heights of 5, 20, 40, 60, 80, and 120 cm (g) and Qt is the total mass of sediment (g) lost from the soil strip during every run. Q was calculated based on measurements of the mass flux qz (mg m-2 s-1) at different heights. The mass transport rate Qr (mg m-1 s-1) was then analytically estimated by integrating qz with height by:

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Environ Earth Sci (2010) 61:1375–1384

Mass flux q

Fig. 5 Top view of the experimental setup for determining the efficiency of the VCSs

30000

Table 1 Descriptive statistics of the Rc at different heights of poles

25000

Configuration Height (cm) N

20000

CPP

20

40 -0.10 0.68

0.15

0.22 147

CPP

40

40 -0.25 0.66

0.07

0.25 357

15000 y = 1743,5x-1,3866 R2 = 0,8694

10000 5000 0 0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

Height z

Fig. 6 An example of power function fitted to the data of mass flux q versus height z for the CPP configuration. Mean values of the seven replicates are shown as a midpoint of the error bars. Mass flux q (g m-2) and height z (m)

Qr ¼

Zh qz dz

ð7Þ

0

where z is the height above the soil surface (m) and h the maximum transport height (1.20 m in our study). A power function was used for curve fitting (Fig. 6) as it provided a better fit to the data than those of Williams (1964) and Sterk and Raats (1996) (exponential model and fourparameter model, respectively): qz ¼ qo za

ð8Þ

where qo is the extrapolated mass flux at the height z = 0 (mg m-2 s-1) and a the slope factor (cm-1). With the invariable width of the soil strip (L = 0.35 m) and the runtime (T = 1 s) the quantity of the trapped sediment Q (g) was computed by: Q ¼ Qr LT

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ð9Þ

Min.

Max. Mean SD

CV

CPP

80

40 -0.09 0.75

0.20

0.23 115

WSP1

20

40 -0.13 1.00

0.16

0.26 162

WSP1

40

40 -0.19 1.00

0.14

0.25 178

WSP1 WSP2

80 20

40 -0.17 0.87 40 -0.23 0.82

0.17 0.10

0.22 129 0.22 220

WSP2

40

40 -0.33 0.83

0.07

0.26 371

WSP2

80

40 -0.17 0.86

0.23

0.25 113

SD standard deviation, CV coefficient of variation, CPP circular plastic pole arrangement of a VCS with a horizontal frame on a pole, WSP1 wooden square pole arrangement of a VCS with pushpins on a pole, WSP2 wooden square pole arrangement of a VCS with a vertical frame on a pole

Results and discussion Descriptive statistics of the Rc around VCS catchers Descriptive statistics of the Rc are given in Table 1. These statistics are means and standard deviations with minimum and maximum values and coefficients of variation (CV) for 40-point measurements at each VCS height. Of the configurations, the WSP2 had the lowest CV at the VCS height of 80 cm, while the WSP2 had the highest value at the height of 40 cm. There was such a noticeable trend in the CV with the VCS heights that it significantly increased at the heights of 40 cm of all configurations when compared to the values of the heights of 20 cm and rapidly decreased again at the heights of 80 cm, where the lowest values were observed among the heights for all configurations. This indicated that significant wind disturbances occurred at the

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height of 40 cm and wind streams were much smoother at the VCS heights of 20 and 80 cm. Geostatistical analysis of the Rc around VCS catchers Table 2 shows the variogram models and parameters for the Rc. A spherical model fitted well to the Rc calculated for the WSP2 at the height of 40 cm, while Gaussian models were used for other configurations (CPP and WSP1) at all heights. The nugget effects indicated that the sampling design was sufficient, and because of the low nugget effects for each variable, the measurement errors were very low for these experiments. The Rc showed different degrees of spatial correlation for each pole and each height. The highest spatial correlations were 27.6 cm for the WSP1 at the height of 20 cm, 77.0 cm for the WSP2 at the height of 40 cm, and 25.2 cm for the CPP at the height of 40 cm. The lowest spatial correlations were 15.6 cm for the WSP1 at the height of 80 cm, 29 cm for the WSP2 at the height of 80 cm, and 22.5 cm for the CPP at the height of 20 cm. Besides, the geostatistical analysis specified that the WSP2 had a higher spatial correlation for every height than the CPP and the WSP1. The WSP2 had a larger surface area due to its attachment geometry for fixing a VCS on a pole. This larger surface area increased wind pressure and therefore could increase the spatial correlation of the Rc. Greater surface roughness intensified the wind turbulence in the neighborhood of the pole. The WSP1 and the WSP2 had different spatial correlations for each height, while the CPP had similar values (Table 2). In terms of the measurement height, there was an evident uniformity in the spatial correlation for the CPP. Aerodynamically, this could be attributed to circular shape of the pole. On the other hand, The Rc of the WSP2 was quite variable with height. In this height, the difference between u and uw increased significantly, indicating a relatively large rise in u with respect to uw . This was less

pronounced for the WSP1 and the CPP, and a decrease in the Rc with height was observed. As mentioned above, the turbulence resulting from the pole shape and the VCS arrangement geometry could affect the degree of variation in the Rc. Therefore, of all, the WSP2 caused the largest scale disturbance in wind. Spatial variation of the Rc around VCS catchers Spatial patterns of the Rc are given in Fig. 7. There were more variations in the Rc in the windward side of both WSP1 and WSP2 than that of the CPP at each height. However, in the leeward side of the poles the opposite occurred, and there were fewer variations in the Rc of both WSP1 and WSP2 compared to the CPP at each height. Again, the spatial variation of the Rc was directly related to a VCS and its arrangement on a pole. The catch efficiency of a VCS could be significantly affected by the spatial distribution of the Rc in the surrounding area of poles, particularly by the wind speed disturbances at the front of a pole. The higher Rc, or the lower the wind speed was, the more the momentum of windblown particles was reduced, which could, to a great extent, reduce the catching efficiency of a VCS, especially for small dust particles. The effect of pole arrangements on the efficiency of VCS catchers Table 3 shows the mean and the standard deviation of the VCS catch efficiency (g, Eq. 6) of the WSP1, WSP2, and CPP configurations. Although the CPP tended to slightly overestimate the amount of windblown particles, it, together with the WSP1, performed much better than the WSP2. The overestimation of g for the CPP could be due to an overestimation of qo in curve fitting of Eq. 8 to the data. A DUNCAN test showed that the mean values of g for three VCS catcher and pole configurations were significantly

Table 2 Variogram models and parameters of the Rc Design CPP

WSP1

WSP2

Height (cm)

Model

Nugget (Co)

Sill (Co ? C)

Range (cm)

r2

20

Gaussian

0.0001

0.058

22.5

0.436

40

Gaussian

0.001

0.071

25.2

0.355

80

Gaussian

0.001

0.060

23.2

0.436

20

Gaussian

0.002

0.063

27.6

0.268

40

Gaussian

0.002

0.068

19.8

0.205

80

Gaussian

0.0001

0.053

15.6

0.331

20

Gaussian

0.0001

0.053

37.7

0.271

40 80

Spherical Gaussian

0.002 0.002

0.074 0.070

77.0 29.0

0.469 0.651

CPP circular plastic pole arrangement of a VCS with a horizontal frame on a pole; WSP1 wooden square pole arrangement of a VCS with pushpins on a pole, WSP2 wooden square pole arrangement of a VCS with a vertical frame on a pole

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Fig. 7 Top view of the kriging maps of the Rc (a, b, and c for CPP; d, e, and f for WSP1, and g, h, and i for WSP2 at the heights of 20, 40, and 80 cm, respectively)

Table 3 Pole shape effect on the efficiency of the VCS (p \ 0.05) (n = 7) CPP Efficiency (g)

A

1.13 ± 0.07

WSP1 B

0.94 ± 0.09

WSP2 0.63C ± 0.14

CPP circular plastic pole arrangement of a VCS with a horizontal frame on a pole, WSP1 wooden square pole arrangement of a VCS with pushpins on a pole, WSP2 wooden square pole arrangement of a VCS with a vertical frame on a pole Different letters indicate significantly different values at p = 0.05 according to a DUNCAN test

123

different (P \ 0.05): the g undoubtedly changed with the pole shape and the configuration of the VCS attachment on a pole. The fact that the higher Rc occurrence in the windward side of the WSP2 (Fig. 7d–f), which was associated with its larger roughness compared to the WSP1 and the CPP, resulted in a lower g. This suggested that the pressure distribution around the catcher played a significant role in its ability to trap windblown particles and to a higher extent that the WSP2 obstructed the pathways of the sediment-laden wind. The relatively lower surface area and

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Table 4 Windblown particles trapped by the surface of VCS catchers per particles size range Particle size (lm)

CPP (mg m-2)

WSP1 (mg m-2)

WSP2 (mg m-2)

0–20

2,095 ± 433

600 ± 303

355 ± 57

20–40

10,352 ± 1,537

7,198 ± 1,827

6,743 ± 1,123

40–60

13,804 ± 2,235

10,609 ± 1,803

12,197 ± 2,499

60–80

8,159 ± 1,223

7,667 ± 2,080

6,757 ± 1,804

80–100

9,038 ± 1,915

7,972 ± 2,509

7,347 ± 1,304

Total

43,450 (2,156 mg)a

34,047 (2,650 mg)

33,398 (3,205 mg)

CPP circular plastic pole arrangement of a VCS with a horizontal frame on a pole; WSP1 wooden square pole arrangement of a VCS with pushpins on a pole, WSP2 wooden square pole arrangement of a VCS with a vertical frame on a pole a

Values in parentheses are total blown particles from the soil strip

roughness of the WSP1 and the CPP compared to the WSP2 (Fig. 3) and the circularly designed shape of the CPP resulted in a lower disturbance of the air flow. Especially, the CPP provided a smaller difference between u and uw or a smaller Rc range (Table 2) in the windward side of the pole at each height (Fig. 7g–i). Of course, not only can the spatial distributions of the Rc at the front but also those at the right and left sides explain the value of g. The increase in u compared to uw (Rc \ 0) at the sides of the CPP illustrated a higher aerodynamic performance, hence contributing to a higher g. Particle size distributions of the sediments trapped by VCS catchers Table 4 shows the amounts of the trapped sediment for different particle size ranges for each configuration. The CPP had the highest catching ability (2,095 mg m-2) for the fraction of 0–20 lm although the CPP test runs produced the lowest amount of total blown soil (2,156 mg). This was strongly related to the aerodynamic shape of the CPP which decreased the Rc in front of a pole. The WSP1 and the WSP2 trapped much less of the finest fraction (respectively, 355 and 600 mg m-2) compared to the CPP. An analogous trend was observed when considering the fraction of 20–40 lm though less pronounced. With respect to the other fractions, the CPP always trapped the highest amounts although differences among the configurations are still small.

Conclusions A series of wind tunnel experiments were performed to examine the effect of three different arrangements of the VCS catcher on the certain types of poles on aerodynamic characteristics around the configurations and the efficiency of VCS (g) in trapping windblown particles at free stream wind speed of 11 m s-1. A geostatistical design for wind speed measurements in vicinity of the poles provided the

spatial distribution of the wind disturbance, which was evaluated by a wind reduction coefficient (Rc). g values of the VCSs used in each configuration were determined by a setup for catching sediments windblown from a sandy loam soil strip. The results showed that the spatial distribution of the Rc and the aerodynamic surface roughness noticeably varied with the pole shape and the geometry of the VCS attachment, resulting in different values of g. The mean of g for the circular plastic pole (CPP) on which a VCS was attached by horizontal pieces of wood arrangements was significantly (P \ 0.05) different from those for the square wooden pole on which a VCS was attached by pushpins attachment (WSP1) and the square wooden pole on which a VCS was attached by vertical pieces of wood arrangement (WSP2). The mean values of g for CPP, WSP1, and WSP2 were 1.13 ± 0.07, 0.94 ± 0.09, and 0.63 ± 0.14, respectively. Moreover, the CPP showed a much higher ability of catching the finest particles (0–20 lm) compared to the WSP1 and the WSP2. These results finally revealed that the saltation and suspension trapping efficiency of the VCS catchers mainly depended upon the aerodynamic characteristics of the resultant geometry of the pole shape and the VCS attachment.

References Bagnold RA (1941) The physics of blown sand and desert dunes. Chapman & Hall, New York Bagnold RA (1954) Physical aspects of dry deserts. In: CloudsleyThompson JL (ed) Biology of deserts. Institute of Biology, London, pp 7–12 Chandler DG, Saxton KE, Kjelgaard J, Busacca AJ (2002) A technique to measure fine-dust emission potentials during wind erosion. Soil Sci Soc Am J 66:1127–1133 Cornelis W, Gabriels D (2003) Optimal windbreak design for winderosion control. J Arid Environ 61:315–332 Cornelis W, Erpul G, Gabriels D (2004) The I.C.E. wind tunnel for wind and water interaction research. In: Visser S, Cornelis W (eds) Wind and rain interaction in erosion. Wageningen University Research Center, Wageningen, pp 195–224

123

1384 De Ploey J (1980) Some field measurements and experimental data on wind-blown sands. In: De Boodt M, Gabriels D (eds) Assessment of erosion. Wiley, Chichester, pp 143–151 Drew RT, Lippmann M (1978) Calibration of air sampling instruments. In: Air sampling instruments for evaluation of atmospheric contaminants, vol I, 5th edn. American Conference of Governmental Industrial Hygienists, Cincinnati, pp 1–138 Fryrear DW (1986) A field dust sampler. J Soil Water Conserv 41(2):117–120 Gabriels D, Cornelis WM, Pollet I, Van Coillie T, Ouessar M (1997) The I.C.E. wind tunnel for wind and water erosion studies. Soil Technol 10:1–8 Gillette DA, Walker TR (1977) Characteristics of airborne particles produced by wind erosion of sandy soil, High Plains of west Texas. Soil Sci 123:97–110 Goossens D, Offer ZY (2000) Wind tunnel and field calibration of six Aeolian dust samplers. Atmos Environ 34(7):1043–1057 Goossens D, Riksen MJPM (2004) Wind erosion and dust dynamics at the commencement of the 21st century. In: Goossens D, Rinksen MJPM (eds) Wind erosion and dust dynamics: observations, simulations, modelling. ESW Publications, Wageningen, pp 7–13 Goossens D, Offer ZY, London G (2000) Wind tunnel and field calibration of five Aeolian sand traps. Geomorphology 35:233– 252 Jackson DWT (1996) A new instantaneous Aeolian sand trap design for field use. Sedimentology 43(5):791–796 Journel AG, Huijbregts CS (1978) Mining Geostatistics. Academic Press, New York, p 600 Kind RJ (1992) Concentration and mass flux of particles in eolian suspension near tailings disposal sites or similar sources. J Wind Eng Ind Aerodyn 41–44:217–225 Leatherman SP (1978) A new Aeolian sand trap design. Sedimentology 25(2):303–306 Loosmore GA, Hunt JR (2000) Dust resuspension without saltation. J Geophys Res 105:663–672 Matheron G (1965) Principles of geostatistics. Econ Geol 58:1246– 1266 Nickling WG, Neuman CM (1997) Wind tunnel evaluation of a wedge-shaped aeolian sediment trap. Geomorphology 18:333– 345

123

Environ Earth Sci (2010) 61:1375–1384 Niemeyer TC, Gillette DA, Deluisi JJ, Kim YJ, Niemeyer WF, Ley T, Gill TE, Ono D (1999) Optical depth, size distribution and flux of dust from Owens Lake, California. Earth Surf Process Landforms 24:463–479 Shao Y (2000) Physics and modelling of wind erosion. Kluwer, Boston, p 393 Shao Y, Rupach MR, Findlater PA (1993) Effect of saltation bombardment on the entrainment of dust by wind. J Geophys Res 98:12719–12726 Spaan WP, van den Abeele GD (1991) Wind-borne particle measurements with acoustic sensors. Soil Technol 4(1):51–63 Soil Survey Staff (1999) Soil taxonomy. A basic system of soil classification for making and interpreting soil surveys, 2nd edn. USDA, NRCS, Washington, DC Sterk G, Raats PAC (1996) Comparison of models describing the vertical distribution of wind-eroded sediment. Soil Sci Soc Am J 60(6):1914–1919 Visser SM, Sterk G, Ribolzi O (2004) Techniques for simultaneous quantification of wind and water erosion in semi-arid regions. J Arid Environ 59:699–717 Williams G (1964) Some aspects of the aeolian saltation load. Sedimentology 3:257–287 Wilson SJ, Cooke RU (1980) Wind erosion. In: Kirkby MJ, Morgan RPC (eds) Soil erosion. Wiley, Chichester, pp 217–252 Youssef F, Erpul G, Bogman P, Cornelis WM, Gabriels D (2008) Determination of efficiency of Vaseline slide and Wilson and Cook sediment traps by wind tunnel experiments. Environ Geol 55:741–750 Zobeck TM (2002) Field measurement of erosion by wind. Encyclopedia of soil science. New York, Marcel Dekker, pp 503–507 Zobeck TM, Van Pelt RS (2006) Wind-induced dust generation and transport mechanics on a bare agricultural field. J Hazard Mater 132:26–38 Zobeck TM, Sterk G, Funk R, Rajot JL, Stout JE, Van Pelt RS (2003) Measurement and data analysis methods for field-scale wind erosion studies and model validation. Earth Surf Proc Land 28:1163–1188