There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network simulates to estimate the concentration of heavy metals. The third aim is to develop a conceptual theory of training stage of neural networks from the perspective of functional analysis and optimization methods. Within this formulation, learning means to solve a variational problem by minimizing a performance function associated to the neural network. The choice of the objective functional depends on the particular application. On the other side, we suggest modification of the performance function to improve the generalization of the suggested networks and to treat the early stopping and local minima problems. The fourth aim is to compare the performance of aforementioned algorithms with regard to predicting ability. Then applied the suggested technique to estimate the concentration of heavy metals such as: Copper(Cu), Lead(Pb), Cadmium(Cd), Cobalt(Co), Zinc(Zn) and Nickel(Ni) in Baghdad soils. First, sixty four soil samples were selected from a phytoremediated contaminated site located in some zones in Baghdad city (residential, industrial, commercial, agricultural and main roads). Second, a series of measurements were performed on the soil samples and analyzed measuring of concentrations for heavy metals using devices such as : Atomic Absorption Spectrophotometer (AAS), X-Ray Fluorescence (XRF) and Inductively Coupled Plasma-Mass Spectrometry (ICP- MS) to get initial concentrations for those heavy metals. Third, simulate and train the suggested networks to get the concentration of heavy metals. The performance of the suggested networks was compared with the traditional laboratory inspecting using the training and test data sets. The results of this book show that the suggested networks trained on experimental measurements can be successfully applied to the rapid and accuracy estimation of concentration of heavy metals. Finally, we suggest some methods for the treatment of contaminated soil by using some herbal plants
Doppler broadening of the 511 keV positron annihilation ??? ? was used to estimate the concentration of defects ?? different deformation levels of pure alnminum samples. These samples were compressed at room temperature to 15, 22, 28, 38,40, and 75 % thickness reduction. The two-state ^sitron-trapping model has been employed. 'I he s and w lineshape parameters were measured using high-resolution gamma spectrometer with high pure germanium detector of 2.1 keV resolution at 1.33 MeV of 60Co. The change of defects concentration (Co) with the deformation level (e) is found to obey an empirical formula of the form Cd - A £ B where A and ? are positive constants that depend mainly on the deformation procedure and the temperature at which the def
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting
... Show MoreThe present study was performed to spotlight the potential role of soil bacteria in the Al-Rumaila oil field as a bioindicator of heavy metals pollution. For this purpose, nine soil samples were collected from different sites, with 20cm depth, to assess the pollution status depending on the total and available concentrations of heavy metals. The result indicates pollution of the studied soils with the following metals: Cd, Cu, Fe, Zn, and Pb. The mean of total concentration for all studied metals was higher than the allowed maximum limit based on the international limit:(3.394, 3.994, 39.993, 8844.979,150.372, and 103.347 µg/g), respectively. While measuring the total Metal concentration is important in determining the de
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Abstract. Al-Abbawy DAH, Al-Thahaibawi BMH, Al-Mayaly IKA, Younis KH. 2021. Assessment of some heavy metals in various aquatic plants of Al-Hawizeh Marsh, southern of Iraq. Biodiversitas 22: 338-345. In order to describe the degree of contamination of aquatic environments in Iraq, heavy metals analysis (Fe, Ni, Cr, Cd, Pb, and Zn) was conducted for six aquatic macrophytes from different locations of Al-Hawizeh Marsh in southern Iraq. The six species were Azolla filiculoides (floating plant), Ceratophyllum demersum, Potamogeton pectinatus, Najas marina (submerged plants), Phragmites australis, and Typha domingensis (emergent plants). The results indicate that cadmium, chromium, and iron concentrations in aquatic plants were above the
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Road-side dust samples were collected during August in 2020 from selected areas of, Al-Rusafa, Baghdad, Iraq. A sedimentological and mineralogical analysis of street dust was conducted. Three areas were selected to study street dusts which are Al-Baladitat, Al-Obaidi and Ziona. The laboratory analyses were done in the Department of Geology, College of Science, University of Baghdad. The heavy metal contents were determined in the roadside dust using XRF Method. It was found that the dust is of muddy texture, and is believed to be transmitted with the various storms blowing on Baghdad or by the wheels of Cars. The results of mineralogical investigation revealed that the dust samples composed of quartz, feldspar, calcite, gypsum and s
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Flame atomic absorption spectrophotometer (FAAS) was used in this study to determine the concentrations of heavy metals such as Ca, Fe, Mn, Cd, Co, Cr, Ni, Cu, Pb and Zn in some food additives of Iraq. The order of metal contents in food additives was found to be Ca ˃ Mn ˃ Fe ˃ Cu ˃ Zn ˃ Pb ˃ Cr ˃ Ni ˃ Co ˃ Cd. The concentration level of each metal was compared with that recommended by food agriculture organisation (FAO) and world health organisation (WHO). Calibration curves were linear for all standard solutions of heavy metals in the range starting from 0.02-0.4 mg/kg for Cd to 11-100 mg/kg for Ca. The correlation coefficients values (R2) of calibrations were investigated and ranged from 0.9971 for Cr to 0.9999 for Ca. Th
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