X-ray diffraction

X-ray diffraction INTRODUCTION: X-ray diffraction The diffraction of X-rays as they pass through a substance, usually forming an interference pattern that can be captured on film and used to analyze the internal structure of the substance. The scattering of x-rays by crystal atoms, producing a diffraction pattern that yields information about the structure of the crystal. X-ray diffraction is used in x-ray crystallography . X-ray diffraction the scattering of X rays by the atoms of a crystal; the diffraction pattern shows structure of the crystal . X-rays are electromagnetic radiation with typical photon energies in the range of 100 eV 100 keV. For diffraction applications, only short wavelength x-rays (hard x-rays) in the range of a few angstroms to 0.1 angstrom (1 keV 120 keV) are used. Because the wavelength of x-rays is comparable to the size of atoms, they are ideally suited for probing the structural arrangement of atoms and molecules in a wide range of materials. The energetic x-rays can penetrate deep into the materials and provide information about the bulk structure. X-rays are produced generally by either x-ray tubes or synchrotron radiation. In a x-ray tube, which is the primary x-ray source used in laboratory x-ray instruments, x-rays are generated when a focused electron beam accelerated across a high voltage field bombards a stationary or rotating solid target. As electrons collide with atoms in the target and slow down, a continuous spectrum of x-rays are emitted, which are termed Bremsstrahlung radiation. The high energy electrons also eject inner shell electrons in atoms through the ionization process. When a free electron fills the shell, a x-ray photon with energy characteristic of the target material is emitted. Common targets used in x-ray tubes include Cu and Mo, which emit 8 keV and 14 keV x-rays with corresponding wavelengths of 1.54 Ã… and 0.8 Ã…, respectively. (The energy E of a x-ray photon and its wavelength is related by the equation E = hc/ï  ¬, where h is Plancks constant and c the speed of light) (check out this ne at animated lecture on x-ray production) In recent years synchrotron facilities have become widely used as preferred sources for x-ray diffraction measurements. Synchrotron radiation is emitted by electrons or positrons travelling at near light speed in a circular storage ring. These powerful sources, which are thousands to millions of times more intense than laboratory x-ray tubes, have become indispensable tools for a wide range of structural investigations and brought advances in numerous fields of science and technology. Powder Diffraction Powder XRD (X-ray Diffraction) is perhaps the most widely used x-ray diffraction technique for characterizing materials. As the name suggests, the sample is usually in a powdery form, consisting of fine grains of single crystalline material to be studied. The technique is used also widely for studying particles in liquid suspensions or polycrystalline solids (bulk or thin film materials). The term powder really means that the crystalline domains are randomly oriented in the sample. Therefore when the 2-D diffraction pattern is recorded, it shows concentric rings of scattering peaks corresponding to the various d spacings in the crystal lattice. The positions and the intensities of the peaks are used for identifying the underlying structure (or phase) of the material. For example, the diffraction lines of graphite would be different from diamond even though they both are made of carbon atoms. This phase identification is important because the material properties are highly dependent on structure (just think of graphite and diamond). Powder diffraction data can be collected using either transmission or reflection geometry, as shown below. Because the particles in the powder sample are randomly oriented, these two methods will yield the same data. In the MRL x-ray facility, powder diffraction data are measured using the Philips XPERT MPD diffractometer, which measures data in reflection mode and is used mostly with solid samples, or the custom built 4-circle diffractometer, which operates in transmission mode and is more suitable for liquid phase samples. A powder XRD scan from a K2Ta2O6 sample is shown below as a plot of scattering intensity vs. the scattering angle 2or the corresponding d-spacing. The peak positions, intensities, widths and shapes all provide important information about the structure of the material. Thin Film Diffraction Generally speaking thin film diffraction refers not to a specific technique but rather a collection of XRD techniques used to characterize thin film samples grown on substrates. These materials have important technological applications in microelectronic and optoelectronic devices, where high quality epitaxial films are critical for device performance. Thin film diffraction methods are used as important process development and control tools, as hard x-rays can penetrate through the epitaxial layers and measure the properties of both the film and the substrate. There are several special considerations for using XRD to characterize thin film samples. First, reflection geometry is used for these measurements as the substrates are generally too thick for transmission. Second, high angular resolution is required because the peaks from semiconductor materials are sharp due to very low defect densities in the material. Consequently, multiple bounce crystal monochromators are used to provide a highly collimated x-ray beam for these measurements. For example, in the Philips MRD used in the x-ray facility, a 4-crystal monochromator made from Ge is used to produce an incident beam with less than 5 arc seconds of angular divergence. Basic XRD measurements made on thin film samples include: Precise lattice constants measurements derived from 2 scans, which provide information about lattice mismatch between the film and the substrate and therefore is indicative of strain stress Rocking curve measurements made by doing a scan at a fixed 2 angle, the width of which is inversely proportionally to the dislocation density in the film and is therefore used as a gauge of the quality of the film. Superlattice measurements in multilayered heteroepitaxial structures, which manifest as satellite peaks surrounding the main diffraction peak from the film. Film thickness and quality can be deduced from the data. Glancing incidence x-ray reflectivity measurements, which can determine the thickness, roughness, and density of the film. This technique does not require crystalline film and works even with amorphous materials. Texture measurementswill be discussed separately The following graph shows the high resolution XRD data of the superlattice peaks on the GaN (002) reflections. Red line denotes results of computer simulation of the structure. Texture Measurement (Pole Figure) Texture measurements are used to determine the orientation distribution of crystalline grains in a polycrystalline sample. A material is termed textured if the grains are aligned in a preferred orientation along certain lattice planes. One can view the textured state of a material (typically in the form of thin films) as an intermediate state in between a completely randomly oriented polycrystalline powder and a completely oriented single crystal. The texture is usually introduced in the fabrication process (e.g. rolling of thin sheet metal, deposition, etc.) and affect the material properties by introducing structural anisotropy. A texture measurement is also referred to as a pole figure as it is often plotted in polar coordinates consisting of the tilt and rotation angles with respect to a given crystallographic orientation. A pole figure is measured at a fixed scattering angle (constant d spacing) and consists of a series of -scans (in- plane rotation around the center of the sample) at different tilt or -(azimuth) angles, as illustrated below. The pole figure data are displayed as contour plots or elevation graphs with zero angle in the center. Below we show two pole figure plots using the same data set. An orientation distribution function (ODF) can be calculated using the pole figure data. Residual Stress Measurement Structural and residual stress in materials can be determined from precision lattice constants measurements. For polycrystalline samples high resolution powder diffraction measurements generally will provide adequate accuracy for stress evaluation. For textured (oriented) and single crystalline materials, 4-circle diffractometry is needed in which the sample is rotated so that measurements on multiple diffraction peaks can be carried out. The interpretation of stress measurement data is complicated and model dependent. Consult the reference literature for more details. Small Angle X-ray Scattering (SAXS) SAXS measurements typically are concerned with scattering angles SAXS measurements are technically challenging because of the small angular separation of the direct beam (which is very intense) and the scattered beam. Large specimen-to-detector distances (0.5 m 10 m) and high quality collimating optics are used to achieve good signal-to-noise ratio in the SAXS measurement. The MRL x-ray facility has cutting edge capabilities for SAXS measurements with three custom-built SAXS instruments including one 3.5-meter long ultra-small angle SAXS instrument with state-of-the-art optics and area detector for low scattering density samples. X-ray Crystallography X-ray crystallography is a standard technique for solving crystal structures. Its basic theory was developed soon after x-rays were first discovered more than a century ago. However, over the years it has gone through continual development in data collection instrumentation and data reduction methods. In recent years, the advent of synchrotron radiation sources, area detector based data collection instruments, and high speed computers has dramatically enhanced the efficiency of crystallographic structural determination. Today x-ray crystallography is widely used in materials and biological research. Structures of very large biological machinery (e.g. protein and DNA complexes, virus particles) have been solved using this method. In x-ray crystallography, integrated intensities of the diffraction peaks are used to reconstruct the electron density map within the unit cell in the crystal. To achieve high accuracy in the reconstruction, which is done by Fourier transforming the diffraction intensities with appropriate phase assignment, a high degree of completeness as well as redundancy in diffraction data is necessary, meaning that all possible reflections are measured multiple times to reduce systematic and statistical error. The most efficient way to do this is by using an area detector which can collect diffraction data in a large solid angle. The use of high intensity x-ray sources, such as synchrotron radiation, is an effective way to reduce data collection time. One of the central difficulties in structural determination using x-ray crystallography is referred to as the phase problem, which arises from the fact that the diffraction data contains information only on the amplitude but not the phase of the structure factor. Over the years many methods have been developed to deduce the phases for reflections, including computationally based direct methods, isomorphous replacement, and multi-wavelength anormalous diffraction (MAD) methods. METHODOLOGY: X-Ray Diffraction Method At Proto we use the x-ray diffraction method to measure residual stress. X-ray diffraction is presently the only portable nondestructive method that can quantitatively measure residual stress in crystalline and semi-crystalline materials. Our high speed x-ray detector technology enables measurements to be performed easily on metals and ceramics; including traditionally difficult materials such as shot peened titanium. XRD uses the coherent domains of the material (the grain structure) like a strain gage which reacts to the stress state existing in the material. Residual stress and / or applied stress expands or contracts the atomic lattice spacing (d). How do we Measure Stress? Actually, we measure strain and convert to stress. The d-spacings are calculated using Braggs Law: ÃŽ » = 2 d sin . If a monochromatic (ï  ¬) x-ray beam impinges upon a sample with an ordered lattice spacing (d), constructive interference will occur at an angle . Changes in strain and thus the d-spacing translate into changes in the diffraction angle measured by the x-ray detectors. The diffraction pattern is in the shape of a cone for polycrystalline materials. The shape of the diffraction peaks can also be related to the dislocation density and coherent domain size. Why Use Multiple Detectors? Unlike other single detector systems. Proto uses two (2) detectors for stress measurements thus capturing both sides of the diffraction cone. This means twice as much data is collected in the same amount of time simply by virtue of the design. Proto offers a four (4) detector system that can be used for both the four peak % retained austenite method and in multiphase stress measurements. Proto also offers 3 and 5 detector configurations for use in Simultaneous Stress and % Retained Austenite determination. Proto adheres to SAE SP-453 Retained Austenite and Its Measurement by X-ray Diffraction and ASTM E975-84 Standard Practice for X-ray Determination of Retained Austenite in Steel with Near Random Crystallographic Orientation.. Patented Fiber Optic Based Solid State Detectors Longevity and Maintenance Proto uses fiber optic based solid state detectors. The fiber optics allow the detector electronics to be remote from the sensing head making them suitable for measurements in harsh environments. Proto detectors are maintenance free and do not degrade with exposure to x-rays, thus less down time, better productivity and no hidden maintenance costs. Direct expose solid state detectors and position sensitive proportional counters degrade with exposure to x-rays and eventually require replacement which can be extremely costly. Because of x-ray damage, these detectors and counters must constantly be re-calibrated. In addition, some position sensitive proportional counters require periodic (bi-annual) maintenance to refill the sealed gas filled detector housing. Speed Proto detectors are the fastest detectors on the market today. A stress measurement can be performed in less than 0.3 seconds, an order of magnitude faster than any other detector technology commercially available. Position sensitive proportional counters can only detect one x-ray event at a time. In addition, there is dead time associated with their signal processing which slows data collection. Proto detectors have no dead time associated with them. They are multi-channel solid state detectors that collect many x-ray events simultaneously resulting in unmatched data collection speed. This is particularly important for laboratories with high throughput demands and for industrial on-line and audit station applications. Drift Position sensitive proportional counters can drift if there is any fluctuation in the DC bias voltage thus causing errors in peak position determination. Ambient temperature fluctuations, gas pressure and oxides on connections, to name a few, can contribute to detector instability and drift. Proto detectors are solid state, thus there is no positional drift associated with them. This means they are much more stable in harsh environments and at elevated or cold temperatures. Detector width Protos wide 2 detector range, 18.7 degrees 2for the 40 mm goniometer geometry offers increased accuracy on materials with broad diffraction peaks found in hardened tool and bearing steels. Flexibility in Residual Stress Measurement Techniques Most systems, particularly one detector systems, offer only double exposure and multiple exposure sin  ²Ã¯  ¹ techniques. Proto systems offer the double exposure and multiple exposure sin  ²Ã¯  ¹ techniques as well as the single exposure technique and the multiple exposure sin  ²Ã¯  £ techniques. This translates into more flexibility for characterizing samples with complicated geometries. Flexibility in Residual Stress Analysis With Proto equipment, unlike other diffraction systems, diffraction peaks can be fit using a number of mathematical functions including, Parabola, Gaussian, Cauchy, Pearson VII, centroid, and mid-chords. Proto also offers both the difference, and cross-correlation methods for peak position determination. This translates into both improved accuracy and flexibility. Focusing Optics Proto systems operate on a true center of rotation and are delivered pre-calibrated to meet exceed ASTM E915-90 Standard Test Method for Verifying the Alignment of X-ray Diffraction Instrumentation for Residual Stress and adhere to SAE J784a Residual Stress Measurement by X-ray Diffraction alignment specifications. All Proto systems operate using parafocusing optics thus eliminating the need for Sollier slits and allowing very fine positional accuracy in stress measurements inside 90 mm and 120 mm i.d. confinements (e.g. the i.d. of pipes and holes, or between parallel surfaces). The competition cannot offer access to such small holes. Simplicity in Use, Sophistication in Results Proto systems are easy to use and setup: Quick change apertures allow for easy adjustment of the irradiated area and sample setup (apertures can be changed in about 2 seconds) with beam dimensions (irradiated area) available from 0.3 mm to 5.0 mm. Sample positioning and focusing can be performed easily using the standoff pointer provided with all systems and through the collimator laser pointer which allows the user to quickly locate measurement locations. This is particularly helpful when using the Automated Stress Mapping option. The 4-Point bending fixture and Proto strain bridge are used for quick and easy determination of the effective x-ray elastic constant for new materials as per ASTM 1426-91, Standard Test Method for Determining the Effective Elastic Parameter for X-ray Diffraction Measurements of Residual Stress. The Proto Portable Electro Polisher is custom manufactured specifically for x-ray diffraction work, making material removal quick and efficient. Truly portable systems are available weighing less than 18 kg (40 lbs). Custom systems are available for customers with special requirements. Comprehensive turnkey systems are offered by Proto to their customers to simplify and expedite their stress measurement needs. Continuous Research and Development and a commitment to give you the best systems in the world. CONCLUSION:  · Other Sectionsââ€" ¼ Abstract 1.Introduction 2.Purification 3.Crystallization 4.X-ray diffraction data collection and analysis 5.Conclusion References Abstract Human phosphate-binding protein (HPBP) was serendipitously discovered by crystallization and X-ray crystallography. HPBP belongs to a eukaryotic protein family named DING that is systematically absent from the genomic database. This apoprotein of 38 kDa copurifies with the HDL-associated apoprotein paraoxonase (PON1) and binds inorganic phosphate. HPBP is the first identified transporter capable of binding phosphate ions in human plasma. Thus, it may be regarded as a predictor of phosphate-related diseases such as atherosclerosis. In addition, HPBP may be a potential therapeutic protein for the treatment of such diseases. Here, the purification, detergent-exchange protocol and crystallization conditions that led to the discovery of HPBP are reported. Keywords: ABC transporters, missing gene, apoproteins, atherosclerosis, paraoxonase  · Other Sectionsââ€" ¼HPBP was serendipitously discovered from supposedly pure PON1. The structure of HPBP (Morales et al., 2006 ) relates it to prokaryote phosphate solute-binding protein (SBP; Tam Saier, 1993; Luecke Quiocho, 1990 ; Vyas et al., 2003), which is associated with the ATP-binding cassette transmembrane transporters (ABC transporters; Higgins, 1992). Despite the existence of the ABC transporter in eukaryotes, SBPs have never been described or predicted by genomic databases in eukaryotes. The complete amino-acid sequence of HPBP (376 amino acids with a predicted molecular weight of 38.4 kDa) was assigned from the electron-density map at the 10% error level (Morales et al., 2006). Surprisingly, the deduced HPBP sequence cannot be retrieved from the human genome or other genomic databases. HPBP is related to a family of eukaryotic proteins that are named DING owing to their four conserved N-terminal residues (Berna et al., 2002). Similarly to HPBP, DING genes are also absent from DNA or RNA databases, although they are likely to be ubiquitous in eukaryotes. This raises numerous questions about the peculiarity of DING genes. The HPBP sequence deduced by crystallography is the first complete sequence of a DING protein and provides a precious basis for understanding the genetic mystery associated with DING proteins. We have provided evidence that HPBP is a new apoprotein mainly located on HDL (good cholesterol) capable of binding inorganic phosphate ions. Furthermore, HPBP presents 59% amino-acid identity with a protein named crystal-adhesion inhibitor (CAI) that may prevent the development of kidney stones by inhibiting the adhesion of calcium oxalate crystals to renal cells (Kumar et al., 2004). Thus, HPBP could be tentatively regarded as a potential predictor and as a possible therapeutic protein for treatment of phosphate-related disorders, including atherosclerosis. In this article, we report the purification, detergent-exchange protocol and crystallization conditions that led to the discovery of HPBP. HPBP was discovered by copurification from an apparently pure PON1 preparation. The HPBP/PON1-containing fractions were obtained according to a protocol based on the method of Gan et al. (1991) (Renault et al., in preparation) that was assumed to provide PON1 pure at ≠¥95%. Briefly, out of date plasma bags from blood donors (Etablissement Franà §ais du Sang Rhà ´ne-Alpes) were supplemented with CaCl2 to a final concentration of 10 mM before the resulting fibrin clot was separated by filtration. The filtrate was then submitted to a pseudo-affinity chromatography on Cibacron Blue 3GA-agarose (type 3000-CL; Sigma) using 50 mM Tris-HCl buffer pH 8.0 supplemented with 1 mM CaCl2 and 3 M NaCl to avoid the adsorption of albumin. Elution of hydrophobic plasma proteins, mainly lipoproteins, was performed using 0.1% sodium deoxycholate and 0.1% Triton X-100 in Tris-HCl buffer. The PON1-containing fractions were pooled and separated from the other HDL-bound proteins, mainly apolipoprotei n A-I, by anion-exchange chromatography on DEAE-Sepharose Fast Flow (Pharmacia Biotech) using 25 mM Tris buffer containing 0.1% Triton X-100 as starting buffer with a gradient of NaCl (0-0.35 M). Pooled HPBP/PON1-containing fractions were dialyzed and concentrated in the presence of C-12 maltoside (0.64 mM) using a centrifugation device (Centriprep Amicon, 10 kDa cutoff, Millipore, St Quentin-en-Yvelines, France) to a final absorbance of 2.3 at 280 nm. Light-scattering analysis revealed a homogeneous sample with an apparent molecular weight of about 80 kDa (Josse et al., 2002 ). This molecular weight was attributed to dimeric PON1 because the existence of HPBP was unknown at this point. Some dialyzed fractions spontaneously crystallized overnight. Crystal plates were very numerous and very thin (about 1  µm width). Once useless crystals had formed in the absence of precipitant agent, it was impossible to dissolve them again. Thus, crystallization trials were performed quickly after detergent exchange. Inspection of the resulting electron-density map clearly indicated that the crystallized protein was not PON1. The sequence deduced from the structure was totally unknown and not predicted by the genomic database. The complete amino-acid sequence was determined from X-ray data. This protein is the first inorganic phosphate transporter characterized in human plasma (Morales et al., 2006). The discovery of this protein by crystallography opens new insight into the physiopathology and medical treatment of phosphate-related diseases RECENTDEVELOPMENTS IN POLYMER CHARACTERIZATION USING X-RAYDIFFRACTION In the absence of an orientational force, thelamellae organize into spherulites (1-10 mm indiameter). X-ray scattering can be used to ob-tain structural information at three lengthscales—1, 10 and 100nm—using scattering atwide-, small- and ultra small-angles, respec-tively.A continuum of structures between the ex-tremesof what are generally regarded as amor-phous and crystalline phases are present in areal polymer, and these entities have complexorganization. But, a model that describes thesemicrystalline polymers in terms of two phases, an average amorphous and an averagecrystalline phase, has been found to be ade-quate for many practical purposes. The fractionof the material that is crystalline, the crys-tallinity or crystalline index, is an important pa-rameter in the two-phase model. Crystallinitycan be determined from a wide-angle X-ray dif- fraction (WAXD) scan by comparing the areaunder the crystalline peaks to the total scatteredintensity [12]. The accuracy and the precision ofthese measurements can be improved by draw-ing a proper base-line, using an appropriateamorphous template, and by carefully choosingthe crystalline peaks [13, 14]. The disorder inthecrystalline domains can be evaluated by measuring the crystallite sizes which are relatedto the radial widths D(2q) of the reflections at ascattering angle 2q by the Scherrer equation. Inreality, there are two contributions to the width:one is the size and the other is the para crystallinity or microstrain [15, 16]. A more detailed analysis based on the Warren-Averbach methodis widely used in metals and ceramics, but lessso in polymers [17]. The disorder in the crys-talline domains is also reflected in the unit celldimensions. But, calculation of the unit cell pa-rameters requires an accurate measurement ofthe positions of many crystalline peaks, which can be difficult. Therefore, in practice, relativepositions of selected crystalline peaks are used as accurate measures of the changes unit cellparameters [18, 19].Structures at length scales larger than a unit cell (10nm instead of 1nm) can be investi-gated using small-angle X-ray scattering(SAXS). The methodology for these analysis isnow highly developed and can be found in anystandard literature [9, 20-24]. While WAXD isused to study the orientation of the crystals,and the packing of the chains within these crys-tals, SAXS is used to study the electron densityfluctuations that occur over larger distances asa result of structural inhomogeneities. SAXS iswidely used to study the lamellar structure bymeasuring parameters such as lamellar spac-ing, height and thickness of the transition layer betweenthe crystalline and amorphous domains. In theanalysis of fibers, SAXS can provide informa-tion about the details of fibrillar morphologysuch as fibril diameter and orientation, and large scale inhomogeneity such as microporesand cracks. This information is somewhat simi-lar to that obtained from a transmission elec-tron micrograph, with one important difference:SAXS requires no sample preparation , and thedata is averaged over the area (typically 0.1mm2) of illumination. SAXS is also used for studying conformation, size and dynamics ofpolymers in solutions and in gels. 3. New Methods to Study Polymer Structure The two-phase model for the polymer hasbeen quite useful in providing a qualitative un-derstanding of the polymer properties in termof its structure, but is not adequate for quantita-tive prediction of the polymer properties. For this purpose, a detailed knowledge of the char-acteristics and distribution of soft (amorphous) and hard (crystalline) domains, and the interac-tions between these domains is necessary. New techniques that have been introduced duringthe past decade provide precisely this informa- tion. Some of these techniques will be discussed here. 3.1. Microbeam Diffraction Microbeam diffraction, or microdiffraction,has been used in semiconductor industry for over 25 years [25]. It is now being used to ex-amine polymeric materials. In most routine characterization of polymers, it is assumed thatthe structure is homogeneous. But, this is not always the case. Temperature gradients are pre-sent during injection molding, and both temper- ature and stress gradients are present duringextrusion and drawing. These gradients intro- duce structural inhomogeneities that influencepolymer performance. Even filaments that are only 10 mm in diameter show variations in ori-entation and density across the cross section [5, 26]. These structural gradients, and the changesin these gradients during deformation can now be studied at spatial resolutions as small as1 mm using microbeam diffraction [26]. An ex- ample of the typical structural gradients presentin a shown in Figure 2 [6]. This diffractogram was obtained from KevlarTM fiber with a 3 mm 16 Synchrotron Radiation Facility) synchrotronsource. The data show that the Hermans orien- tation function of the crystalline domains in this12 mm diameter fiber increases from 0.955 at the center to 0.980 at the surface of the fiber.The higher orientation of the skin layer is obvi- ously due to large shear stresses at the spin-neret, extensional forces in the air-gap and the solidification in the coagulation bath. Such astructural gradient implies that the modulus de- creases from the skin to core. It is interesting tonote that these inhomogeneities gradually de- crease and disappear under uniaxial stress.Microbeam techniques have reached a level of sophistication that it is now possible to focus .X-rays on a micron size crystal and follow the changes in the structure from one crystal to t

The Business of Offshore Outsourcing in India :: Globalization essays, research papers

Offshore outsourcing of IT and business process outsourcing (BPO) is known to be the practice of hiring an external organization to perform some or all business functions in a country other than the one where the product or service will be sold or consumed. â€Å"In 2005 IT and BPO were estimated to have generated revenues of $36 billion contributing nearly 5% of the GDP† (â€Å"Virtual,† 2006, p. 1). It is very clear that BPO has transformed into a very large and profitable business, with â€Å"India leading the way by providing $7.5 billion in BPO revenue this year. India’s outsourcing capabilities have grown steadily throughout the last decade† (â€Å"Turning India,† 2006, p. 1). â€Å"In the 1980’s outsourcers in India did low skill jobs such as data entry and some software development. In the 1990’s they expanded by doing larger software projects, taking over entire IT systems and back office functions such as accounting for U.S. and European corporations † (â€Å"Offshoring,† 2006, p.1). â€Å"Indian IT grew on the relatively humdrum software work needed to fix the Y2k millennium bug at the end of the 20th century. It then received a boost from the dotcom bust, which in many firms in America and elsewhere caused IT budgets to be slashed, prompting outsourcing to India for a lower price† (â€Å"Virtual,† 2006, p. 1). The India of today has taken on new challenges and more sophisticated services such as engineering, research and development, and designing auto parts, and chips for wireless service (â€Å"Offshoring,† 2006, p. 1). â€Å"Now Indian firms can perform almost every service offered by the global giants of IT outsourcing and India’s core business remains â€Å"ADM† which is the application, development and maintenance of software, which accounts for about 55% of exports of IT services†(â€Å"Virtual,† 2006, p.1). Tata Consultancy Services, Infosys, and Wipro are the three largest Indian IT service firms in India, â€Å"Each are recruiting and hiring more than 1,000 people per month† (â€Å"Next Wave,† 2006, p. 1). J.P. Morgan Chase, a large investment bank in the U.S., plans to double its staff to 9,000 in the near future. These new employees responsibility will be to settle complex structured finance and derivative deals (â€Å"Next Wave,† 2006 p. 1). These new investments all show that India has moved into a third stage of the great Indian services-export boom. In the first stage, â€Å"firms such as Tata developed world-class expertise in software application development, and maintenance. The Business of Offshore Outsourcing in India :: Globalization essays, research papers Offshore outsourcing of IT and business process outsourcing (BPO) is known to be the practice of hiring an external organization to perform some or all business functions in a country other than the one where the product or service will be sold or consumed. â€Å"In 2005 IT and BPO were estimated to have generated revenues of $36 billion contributing nearly 5% of the GDP† (â€Å"Virtual,† 2006, p. 1). It is very clear that BPO has transformed into a very large and profitable business, with â€Å"India leading the way by providing $7.5 billion in BPO revenue this year. India’s outsourcing capabilities have grown steadily throughout the last decade† (â€Å"Turning India,† 2006, p. 1). â€Å"In the 1980’s outsourcers in India did low skill jobs such as data entry and some software development. In the 1990’s they expanded by doing larger software projects, taking over entire IT systems and back office functions such as accounting for U.S. and European corporations † (â€Å"Offshoring,† 2006, p.1). â€Å"Indian IT grew on the relatively humdrum software work needed to fix the Y2k millennium bug at the end of the 20th century. It then received a boost from the dotcom bust, which in many firms in America and elsewhere caused IT budgets to be slashed, prompting outsourcing to India for a lower price† (â€Å"Virtual,† 2006, p. 1). The India of today has taken on new challenges and more sophisticated services such as engineering, research and development, and designing auto parts, and chips for wireless service (â€Å"Offshoring,† 2006, p. 1). â€Å"Now Indian firms can perform almost every service offered by the global giants of IT outsourcing and India’s core business remains â€Å"ADM† which is the application, development and maintenance of software, which accounts for about 55% of exports of IT services†(â€Å"Virtual,† 2006, p.1). Tata Consultancy Services, Infosys, and Wipro are the three largest Indian IT service firms in India, â€Å"Each are recruiting and hiring more than 1,000 people per month† (â€Å"Next Wave,† 2006, p. 1). J.P. Morgan Chase, a large investment bank in the U.S., plans to double its staff to 9,000 in the near future. These new employees responsibility will be to settle complex structured finance and derivative deals (â€Å"Next Wave,† 2006 p. 1). These new investments all show that India has moved into a third stage of the great Indian services-export boom. In the first stage, â€Å"firms such as Tata developed world-class expertise in software application development, and maintenance.

Study on Infiltration and Soil Texture Under Banana and Maize Land Use Systems in Gatundu Catchment, Kiambu County, Kenya

KENYATTA UNIVERSITY SCHOOL OF PURE AND APPLIED SCIENCES DEPARTMENT OF GEOGRAPHY STUDY ON INFILTRATION AND SOIL TEXTURE UNDER BANANA AND MAIZE LAND USE SYSTEMS IN GATUNDU CATCHMENT, KIAMBU COUNTY,KENYA KAKAIRE JOEL I56EA/20023/2012 ICEDUNA MARION I56EA/20021/2012 MWM714: FIELD MAPPING AND LABORATORY TECHQNIUES FIELD REPORT COURSE INSTRUCTOR: DR. MAKOKHA GEORGE TABLE OF CONTENTS CONTENTS PAGES 1. 0 Introduction †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 1 1. Significance of the study †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 2 1. 2 Objectives †¦Ã ¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 2 1. 2. 1 Specific Objectives †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 2 2. 0 METHODS AND MATERIALS †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 3 2. INTRODUCTION†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 3 2. 2 Study area †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 3 2. 3 Research design†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 6 2. 4 Data collection procedures and laboratory analysis †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 6 2. 4. Soil Texture †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 6 2. 4. 2 Infiltration †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 7 3. 0 RESULTS AND DISCUSSIONS †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 8 3. 1 Soil Infiltration Measurements †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â ‚¬ ¦Ã¢â‚¬ ¦. 8 4. CONCLUSION AND RECOMMENDATION †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 13 5. 0 REFERENCES†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 15 APPENDIX †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 17 Appendix 1: Data sheet for Infiltration for Banana and Maize Fields †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 17 ii LIST OF FIGURES Figure 1: I nfiltration Curve of Banana field †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦. 0 Figure 2: Cumulative Infiltration of Banana Field †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 10 Figure 3: Infiltration curve of Maize Field †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 11 Figure 4: Cumulative infiltration of Maize Field†¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 11 iii LIST OF TABLES Table 1: Description of infiltration sites †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã ¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 8 Table 2.Summary of the soil texture report from the test sites †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦.. 12 LIST OF PLATES Plate 1: Infiltration in Banana and Maize field respectively †¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦Ã¢â‚¬ ¦ 7 iv v 1. 0 Introduction Water is one of the most important factors limiting the growth of plants in all Agricultural systems. In this respect, good water management is necessary in order to solve water related problems such as irrigation and erosion control. Infiltration is the process by which water arriving at the soil surface enters the soil.This process affects surface runoff, soil erosion, and groundwater recharge (Gregory et al. , 2005). The rate at which it occurs is known as infiltration rate which mainly depends on the characteristics of the soil. ( Saxton, 1986) reported that, the major soil and water characteristics affecting infiltration rates are: the initial moisture content, condition of the surface, hydraulic conductivity of the soil profile, texture, porosity, degree of swelling of soil colloids, organic matter, vegetative cover and duration of irrigation or rainfall and of these, soil texture is predominant.Therefore the measurement of water infiltration into the soil is an important indication in regard to the efficiency of irrigation and drainage, optimizing the availability of water for plants, improving the yield of crops, minimizing erosion and describing the soil permeability. Land use and land cover changes among other factors have also been reported to infuluence the infiltration rate of soil. According to (Suresh, 2008), for a given soil, the land use pattern plays a vital role in determining i ts infiltration characteristics.Different land use practices affect infiltration rates in different ways. (Taylor et al, 2009), observed that intensified land use results primarily in a change in soil structure rather than soil compaction. When land is put to certain uses, there is an accompanying change in the properties of the soil and this alters the hydrological balance of the soil. According to (Osuji, 2010) infiltration rates in tropical forests under bush fallow were found to be high compared to arable crop land. In addition, Majaliwa et al. 2010) explains that the change from natural forest cover to tea and Eucalyptus induces changes in top soil properties like exchangeable Magnesium and Calcium, available Phosphorus, soil organic matter, soil pH, and soil structure of sub soil. Furthermore, Land use/type cover influences soil organic matter evolution which is a vital indicator of soil quality and it has implications on soil properties like aggregate stability/soil structure , infiltration and aeration rates, microbial activity and nutrient release (Boye and 1Albrect, 2001). Additionally a soil’s water retention characteristic, is affected by soil organic matter (SOM) content and porosity, which are significantly influenced by land use type (Zhou et al. , 2008). Gatundu catchment is one of the catchments in Kenya which have experienced soil degradation due to conversion of natural forest to crop land mainly banana, maize and Coffee. This has been fastened by the increasing population in the catchment leaving most of the natural forest cover cleared and replaced by crop land.The result has been massive soil degradation, through loss of plant nutrients and organic matter, soil erosion, river bank degradation; build up of salinity, and damage to soil structure (Bekunda et al. , 2010). Therefore this study aims to determine the degree of relationship between infiltration rates and the land use types in two selected sites under Banana and Maize croppi ng systems in Gatundu sub catchment. 1. 1 Significance of the study The knowledge of water retention capacity and land use effects is important for efficient soil and water management.Upon conversion of natural lands to cultivated fields, water retention capacity is strongly influenced (Schwartz et al. , 2000; Bormann and Klaassen, 2008; Zhou et al. , 2008). Thus, infiltration rate is an important factor in sustainable agriculture, effective watershed management, surface runoff, and retaining water and soil resources. Properly designed and constructed infiltration facilities can be one of the most effective flow control (and water quality treatment) storm water control practices, and should be encouraged where conditions are appropriate (Ecology, 2005) 1. Objectives The objective of the study is to determine the effect of banana and Maize land use practices on water infiltration into the soil in Gatundu catchment 1. 2. 1 Specific Objectives 2 1. 2. Describe how different soil types influence water flow through the soil Compare Water movements through the soil at two different sites (Banana and Maize fields) 3. To find out how soil texture influences water infiltration into the soil 2. 0 METHODS AND MATERIALS 2. INTRODUCTION This section covers the methods and materials used in the study which include description of the study area, experimental design, field data collection procedures for soil samples and data analysis procedures; laboratory and statistical data analysis using Microsoft office package. 2. 2 Study area Gatundu district is one of the districts located in central province of Kenya at 1 ° 1†² 0†³ South, 36 ° 56†² 0†³ East; covering an area of 481. 1 km2 and borders Thika district to the East and North and Kiambu East to the South and West (Figure 5).The population density varies from 370 persons per Km2 in Chania and Mangu divisions to 636 persons per Km2 in Gatundu division on the 2008 population projections. Gatundu divisi on is the most densely populated division with 636 persons per square Km. The population over the plan period is expected to increase marginally thereby increasing demand and competition for the available resources like water and land resources (Gatundu District Development plan, 2008 -2012). 3 ` Figure 5: Map of Gatundu south Topography features of Gatundu district Gatundu district is located about 1520 m ASL at the lowest point and 2280 m ASL at the highest point.There are several permanent rivers and streams that traverse the landscape and these include Ndaruga, Thiririka, and Kahuga. All these rivers flow from the Aberdare ranges to the west and towards the southeast joining River Tana thus forming part of Tana and Athi river 4 drainage system. The train is conducive for gravity system of irrigation (Gatundu District Development plan, 2008 -2012). Terrain Gatundu district is characterized by a ragged terrain, which has had both the negative and positive impacts on the developmen t of the district.The steep slopes and valleys characteristic of the most part of the district, coupled with intensive crop cultivation render most of these areas susceptible to soil erosion making it necessary for farmers to practice terracing which is costly. The conducive environment in the district favour the cultivation of tea and coffee however, other crops like cereals, horticultural crops such as pineapple, mangoes, avocadoes and vegetables plus bananas (Gatundu District Development plan, 2008 -2012). Soils Gatundu district has soils that correspond entirely with typical Aberdare Humic Andosols and Nitosols.These Nitosols have great agricultural potential coupled with the relatively high rainfall regime in the region. Production of tea, coffee, tropical fruits and food crops such as maize, beans and potatoes are the most common sources of income to the households. The hilly terrain of the district has had profound effect on the soils, resulting into low and moderate fertilit y levels (Gatundu District Development plan, 2008 -2012). Climate The rainfall pattern is bi-modal with two distinct rainy seasons, long rains falling in March and May while short rains between October and November.The amount received varies with altitude ranging from 800 mm to 2000 mm with the highest rainfall being experienced in the tea zones. The mean temperature is 200 C with coldest months being June, July and August. The hottest months are February, March and April. Temperatures vary from 80C minimum to 300 C maximum during the year. (Gatundu District Development plan, 2008 -2012) 5 2. 3 Research design A completely randomized block design was used for the study. Two treatments were considered (Banana and Maize land uses) and the blocking was landscape position. For Each land use type, only one experiment was carried out because of time. . 4 Data collection procedures and laboratory analysis 2. 4. 1 Soil Texture Five (5) soil samples from both Banana and Maize land uses at di fferent landscape positions were collected. The sampling was done at depth of 0 -15 cm and were collected using a 50 mm diameter auger using a Random sampling Technique as explained by Haghighi et al. (2010) . The 0-15cm depth was considered because it’s the major agricultural layer and root zone for most of the crops. The five soil samples from each land use were thoroughly mixed to obtain composite soil samples which were taken to Makerere University Laboratory for Analysis.Soil texture was determined using the hydrometer method described by Bouyoucos (1962) and results presented in percentages of mineral proportions. The samples were passed through an electric shaker for 30 minutes and then the sample was treated with sodium hexametaphosphate to complex Ca++, Al3+, Fe3+, and other cations that bind clay and silt particles into aggregates. The density of the soil suspension was determined with a hydrometer which was calibrated to read in grams of solids per liter after the sand settled out and again after the silt settled. Corrections were made for the density and temperature of the dispersing solutions.The percentages of mineral fractions were calculated as below; Percent clay: % clay = corrected hydrometer reading at 6 hrs, 52 min. x 100/ wt. of sample Percent silt: % silt = corrected hydrometer reading at 40 sec. x 100/ wt. of sample – % clay Percent sand: 6 % sand = 100% – % silt – % clay Results were reported as percentages of the mineral fraction, % sand, % silt, and % clay. Soil texture was based on the USDA textural triangle. 2. 4. 2 Infiltration The infiltration rate was determined using double-ring infiltrometer as described by American Society for Testing and Materials (1994).It consists of two concentric metal rings. The rings were driven into the ground and filled with water. The outer ring helped to prevent divergent flow. The drop-in water level or volume in the inner ring was used to calculate the infiltration rate . Clock time was recorded when the test began and noted the water level on the ruler at different time intervals as seen in Appendix 1, recorded the drop in water level in the inner ring on the ruler and kept adding water to bring the level back to approximately the original level.The tests were conducted for a period of one to two hours, until the infiltration rate became constant. The infiltration rate was calculated from the rate of fall of the water level in the inner ring as seen in Appendix 1 in the tenth minutes in both the banana field and maize fields. The data was analyzed by drawing graphs of infiltration rate and cumulative infiltration. In both cases, curves were obtained. Plate 1: Infiltration in Banana and Maize field respectively 7 3. 0 RESULTS AND DISCUSSIONS 3. Soil Infiltration Measurements Soil infiltration measurements were made at 2 sites in Gatundu sub catchment (Plate 1 above). The two sites have the same soil characteristics, therefore they have been classif ied by the different land uses and land scape positions coupled by other field observations. Sites were selected based on land use, proximity to water source, site accessibility, and soil type. Table 1: Description of infiltration sites Site Location Banana Site Observed and use and field observations Site with Banana plantations, Has some mounds, some trees adjacent to the field, it’s on a higher elevation Maize Site Site with Maize, The site is close to a trench used for moving water, Its close to the road , It’s on a lower elevation Figure 1(Banana land use) and Figure 3(Maize land use) shows that the water infiltrates at a very high rate at the beginning with 1800 mm/hr and 720mm/hr respectively; because the hydraulic gradient is high and then keeps declining with time until it becomes fairly steady after the soils become saturated, which is termed as basic infiltration rate.This is also emphasized by Horton (1940) where he asserts that infiltration becomes constan t with time as the soil column reaches fully saturated conditions which occurred at 40th and 49th minute time intervals in Banana and Maize Land use Systems as seen in appendix 1. Rubin and Steinhardt (1963) also showed that the final infiltration rate reached under these conditions is equal to the vertical hydraulic conductivity of a saturated soil. 8 The steady state in Maize was attained earlier than in banana land use corresponding to 204mm/hr and 450mm/hr respectively.This can be associated to soil disturbances during ploughing and land preparation season after season for annual crops like maize compared to banana field (Perennial) which have less soil disturbances. The scenario under maize land use may lead to soil compaction as a result of continuous cultivation. This is emphasized by Pitt et al. , 2002 and 2008; Pitt et al. , (1999b) who found substantial reductions in infiltration rates due to soil compaction. The implication is that beyond the steady point (saturation poin t), if more water is applied to the soil, it results into surface water runoff.Infiltration depends upon physical and hydraulic properties of the soil moisture content, previous wetting history, structural changes in the layers and air entrapment. The basic infiltration rate of maize land use is lower than that of Banana land use system as seen in Appendix 1; this can be associated to a number of factors although not conclusive for the attained results; 1. The Initial moisture content; the study was carried out in a rainy season, therefore for saturated soils, the infiltration falls to the aturated hydraulic conductivity almost instantaneously. 2. Considering the type of land use in each of the sites; Soils under Perennials (Banana Land use) are subjected to less interferences in terms of land preparations compared to land under annuals (Maize Land use) which correlates with the obtained results of 450mm/hr and 204mm/hr respectively 3. The surrounding of the site; the Maize field is on a lower elevation and near a trench which collects water, therefore it’s possible that the soils could easily reach saturation 9 Infiltration rate mm/hr 000 1800 1600 1400 1200 1000 800 600 400 200 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Infiltration rate,mm/hr infiltration rate mm/hr Time(minutes) Figure 1: Infiltration Curve of Banana field Cummulative infiltration cummulative infiltration,mm 500 450 400 350 300 250 200 150 100 50 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Cummulative infiltration Time,hrs Figure 2: Cumulative Infiltration of Banana Field In Banana land use, Infiltration was recorded at time intervals of 1, 5 and 10 minutes and in Maize land use it was at 3, 6 and 10 minutes time intervals (Appendix 1) 10Infiltration rate/hr 800 Infiltration rate mm/hr 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 Infiltration rate/hr Time,hrs Figure 3: Infiltration curve of Maize Field Cummulative infiltration Cummulative infiltration,mm 350 300 250 200 150 100 50 0 1 2 3 4 5 6 7 8 Cummu lative infiltration Time,hrs Figure 4: Cumulative infiltration of Maize Field 11 Table 2 below compares the infiltration rates of two sites, classified according to the texture of the soil profiles in Banana and Maize land use systems.In each set of measurements, the infiltration rate of the Banana field belonging to the sandy clay loam was much higher than Maize field belonging to clay loam because of the variation in the physical properties of the two textural classes. In the banana field, basic infiltration rate was attained at 450mm/hr which is higher than that of maize field, 204mm/hr and this explains the relationship between soil texture, structure and infiltration which was obtained in our results where the Banana field with sandy clay loams having larger pores allowed in more water to infiltrate compared to clay loam with relatively smaller pores.From our results, The banana field reached saturation earlier (40th minute) than the Maize field (49th minute) which deviates fro m the assumption that the field at lower elevation reaches saturation earlier than the other on the higher elevation, and this case the maize field was on a lower elevation. As it is not possible to vary soil texture independently of other characteristics it is not inferred that the infiltration rates are caused by texture.Table 2 Summary of the soil texture report from the test sites Sample Percentage % Sand Banana Field Maize Field 50 40 Silt 26 26 Clay 24 34 Sand clay loam Clay loam Textural Class 12 4. 0 CONCLUSION AND RECOMMENDATION Generally from the findings, the two sites registered high basic infiltration rates with banana and maize land use having 405mm/hr and 204mm/hr respectively. The two sites as well reached saturation easily because of the amount of water that was held within the soil because of the rainy season.Several factors influenced the test; measuring rapidly changing water levels was difficult especially for one minute time intervals and therefore subject to i naccuracy and the local site features, challenges in elevation and the soils being too soft which kept altering the position of the ruler and varying the depth thus may have affected individual test results. Therefore the study required more data collection and time to be able to sample many sites at different time intervals. For this study, tests were conducted during a rainy period in December, 2012, where the water table was expected to be above most soil layers.However, Infiltration is a key parameter in Watershed management therefore Properly designed and constructed infiltration facilities can be one of the most effective flow control (and water quality treatment) , and should be encouraged where conditions are appropriate (Ecology, 2005). Additionally infiltration separates water into two major components surface runoff and subsurface recharge, therefore assessment and Evaluation of runoff risk has assumed an increased importance because of concerns about associated pollution hazards in which pollutants are likely to be transferred from soil to rivers and lakes.The speed of irrigation of fields is based on infiltration tests and data; in surface irrigation, infiltration changes dramatically throughout the irrigation season. The water movements alter the surface structure and geometry which in turn affect infiltration rates; therefore accurate determination of infiltration rates is essential for reliable prediction of surface runoff. As environmental impact assessments are concerned with long-term effects, it is essential that the 13 infiltration data on which they are based should be reasonably stable. For planning purposes it is essential to know the stability of infiltration data. 4 5. 0 REFERENCES American Society for Testing and Materials, 1994, Standard test method for infiltration rate of soils in field using double-ring infiltrometer: ASTM Publication D-3385-94, 7 p. Bouyoucos, G. J. 1962. Hydrometer method improved for making particle size analy sis of soils. Agron. J. 54:464-465. Ecology (2005) Stormwater Management Manual for Western Washington; Olympia, WA. Washington State Department of Ecology Water Quality Program. Publication Numbers 05-10-029 through 05-10-033. http://www. ecy. wa. gov/pubs/0510029. pdf Gregory, J. H. , Dukes, M. D. , Miller, G. L. , and Jones P.H. (2005) Analysis of double-ring infiltration techniques and development of a simple automatic water delivery system. Applied Turfgrass Science. Haghighi. F. , & Gorjiz, M. & Shorafa M. (2010). Effects of Land Use Change on Important Soil Properties. Land Degrad. Develop. 21, 496–502. Horton, R. E. , 1940, An approach towards a physical interpretation of infiltration capacity: Soils Science Society of America Proceedings, v. 5, p. 399-417. Osuji, G. E,Okon M. A; Chukwuma and Nwaire (2010): Infiltration characteristics of soils under selected landuse practices in Oweri, Southern Nigeria.World journal of Agricultural Sciences 6(3): 322 – 326 Pit t, R. ; J. Lantrip; R. Harrison; C. Henry, and D. Hue (1999b) Infiltration through Disturbed Urban Soils and Compost-Amended Soil Effects on Runoff Quality and Quantity; EPA 600-R-00-016. U. S. Environmental Protection Agency. National Risk Management Research Laboratory. Office of Research and Development. Cincinnati, OH: 231 pp. Pitt, R; Chen, S. -E; Clark, S. E (2002) Compacted Urban Soils Effects on Infiltration and Bioretention Stormwater Control Designs; Proc. , 9th Int. Conf. on Urban Drainage (9ICUD).Portland, Oregon. Pitt, R; Chen, S-E; Clark, S; Swenson, J. , and Ong, C. K (2008) Compaction’s Impacts on Urban Storm-Water Infiltration; J. Irrig. and Drain. Engrg. , 134(5), 652-658. Rubin, J. , and Steinhardt, R. , 1963, Soils water relations during rain infiltration; Part I–Theory: Soils Science Society of America Proceedings, v. 27, p. 246-251 Saxton, K. E. , W. L. Rawls, J. S. Rosenberger and R. I Papendick, 1986. Estimating generalized soil water characteri stics from texture. Soil Sci. Soc. Amer. J. , 50: 1031-1036 15 Schwartz, R. C. , Unger, P. W. Evett S. R. , 2000. â€Å"Land use effects on soil hydraulicproperties. † Suresh, D. (2008). Land and Water Management Principles: New Delhi, Shansi Publishers Taylor, M. , M. Mulholland and D. Thornburrow,2009. Infiltration Characteristics of Soils Under forestry and Agriculture in the Upper Waikato Catchment. Report: TR/18 http:// www. ew. govt. nz/publications/ Technical-Reports/ TR-200918/ Zhou, X. , Lin, H. S. , White, E. A. , 2008. â€Å"Surface soil hydraulic properties in four soil series under different land uses and their temporal changes. † Catena. 73, 180-188. 16APPENDIX Appendix 1: Data sheet for Infiltration for Banana and Maize Fields Banana Field Time Reading clock on difference, Cumulative min time, min Infiltration Water Level, Infiltration, Infiltratio rate cm cm n, mm mm/min Infiltration rate mm/hr Cumulative infiltration, mm 12:32 12:33 12:34 12:35 12:36 1 2:37 12:42 12:47 12:52 12:57 13:02 13:07 1 1 1 1 1 5 5 5 5 5 10 1 2 3 4 5 10 15 20 25 30 40 12. 0 13. 5 13. 8 14. 0 14. 3 9. 4 12. 8 11. 0 12. 0 12. 7 9. 8 15. 0 15. 0 15. 0 15. 0 15. 0 15. 0 15. 0 15. 0 17. 0 17. 3 17. 3 17. 5 3. 0 1. 5 1. 2 1. 0 0. 7 5. 6 2. 2 4. 0 5. 0 4. 6 7. 5 17 30 15 12 10 7 56 22 40 50 46 75

Taking a Look at Global Warming - 754 Words

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