scholarly journals Characterisation of Tailings from Itakpe Iron Ore Mine, Itakpe, Nigeria

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
R.A. Adebimpe ◽  
A.O. Fatoye
Keyword(s):  
Specific Gravity ◽  
Food Chain ◽  
Iron Ore ◽  
Mine Waste ◽  
Cadmium Concentration ◽  
Metal Mobility ◽  
Residual Fraction ◽  
Base Line ◽  
Iron Ore Mine ◽  
Waste Dumps

Knowledge of tailings characteristics is required for utilisation and management purposes in the mining and construction industry. Tailings from the mine waste dumps at Itakpe iron ore mine were collected and analysed in the laboratory to determine their chemical and physical characteristics and these include; permeability, porosity, specific gravity, particle size distribution, chemical composition and bioavailability factor of element. Geochemical speciation with quantitative X-ray powder diffraction was used to evaluate the chemical and mineral composition of Itakpe iron ore tailings. The aim is to offer base line data necessary to assess metal mobility and bioavailability. The distribution of heavy metals such as Cu, Ni, Cd, Cr, Zn and Fe was determined using multi- step sequential extraction. The results obtained indicate that the permeability is 6.24 x 10-3 cm/sec; porosity is 35%; and specific gravity is 3.58. The tailings is well graded and is sand gravel. Nickel and Zinc was found to be considerably high in exchangeable and bound to carbonates fraction which are mobile region and is bound to Fe – Mn oxides which is slightly mobile region but the higher concentration of Ni found in residual fraction. The implication of this result is that Nickel and Zinc partially enter into the food chain. Chromium and Cadmium concentration result indicated that these metals can easily enter into the food chain because of their presence in the mobile region and their higher mobility percentage.

Metallic pollution in clogging materials of urban porous pavements

1995 ◽  
Vol 32 (1) ◽  
pp. 57-62 ◽  
Author(s):  
Valérie Colandini ◽  
Michel Legret ◽  
Yves Brosseaud ◽  
Jean-Daniel Baladès
Keyword(s):  
Heavy Metal ◽  
Particle Size ◽  
Road Traffic ◽  
Total Concentration ◽  
Extraction Procedure ◽  
Interaction Strength ◽  
Metal Mobility ◽  
Residual Fraction ◽  
Metal Contents ◽  
Copper Zinc

Porous pavements infiltrated with stormwater are faced with clogging problems: runoff particles seep and clog the pervious surface layer of these structures. Clogging material samples (in the form of sludge) have been collected in cleaning operations on the pervious asphalt. This study aims at characterizing these materials, particle size distribution, heavy metal contents by particle size, and studying interactions between metals and particles. A sequential extraction procedure proposed by the experts of the Community Bureau of Reference (B.C.R.) was applied to provide information about heavy metal distribution on particles and to evaluate interaction strength, and consequently potential metal mobility when chemical variations occurred in the environment. Mainly made up of sand, the materials are polluted with lead, copper, zinc and cadmium. The concentrations appeared to be linked with road traffic intensity. The heavy metal contents by particle size showed that the finer are the particles, the higher are the heavy metal concentrations. Heavy metals were found potentially labile; metals contents in the residual fraction (mineral fraction) represented less than 20 % of the total concentration. Cadmium and zinc were apparently more labile than lead and copper.

Use of SAR interferometry for monitoring illegal mining activities: A case study at Xishimen Iron Ore Mine

2011 ◽  
Vol 21 (6) ◽  
pp. 781-786 ◽  
Author(s):  
Maowei Ji ◽  
Xiaojing Li ◽  
Shunchuan Wu ◽  
Yongtao Gao ◽  
Linlin Ge
Keyword(s):  
Iron Ore ◽  
Sar Interferometry ◽  
Mining Activities ◽  
Iron Ore Mine ◽  
Illegal Mining

scholarly journals Effects of Moderate Intensity Interval Training in workers suffering from Restrictive Lung Diseases involved in Polluted environment at Iron Ore Mine

2021 ◽  
Vol 18 (1) ◽  
pp. 32-44
Author(s):  
Abdolhakim Batajrobeh Rudi ◽  
Mohsen Mohammadnia Ahmadi ◽  
Mehdi Mogharnasi ◽  
◽  
◽  
...  
Keyword(s):  
Lung Diseases ◽  
Iron Ore ◽  
Interval Training ◽  
Moderate Intensity ◽  
Polluted Environment ◽  
Iron Ore Mine

scholarly journals The Forecasting of Groundwater Fluctuations using Time Series Analysis and Combination of Data-Driven Models

2021 ◽  
Author(s):  
Amirhossein Najafabadipour ◽  
Gholamreza Kamali ◽  
Hossein Nezamabadi-pour
Keyword(s):  
Iron Ore ◽  
Least Squares Method ◽  
Moving Average ◽  
Groundwater Resources ◽  
Mining Area ◽  
Data Driven ◽  
Short Term ◽  
Iron Ore Mine ◽  
Groundwater Fluctuations ◽  
Groundwater Drainage

The Forecasting of Groundwater Fluctuations is a useful tool for managing groundwater resources in the mining area. Water resources management requires identifying potential periods for groundwater drainage to prevent groundwater from entering the mine pit and imposing high costs. In this research, Auto-Regressive Integrated Moving Average (ARIMA) and Holt-Winters Exponential Smoothing (HWES) data-driven models were used for short-term modeling of the groundwater fluctuations in a piezometer around the Gohar Zamin Iron Ore Mine. For this purpose, 250 non-seasonal groundwater fluctuations data in the period 22-Nov-2018 to 29-Jul-2019, 200 data for modeling, and 50 data for prediction were used. To take advantage of all the features of the two developed models, the predictions are combined with different methods and specific weights. The results show better accuracy for the ARIMA method between the two short-term forecasts, while the HWES method requires less time for modeling. Also, among all the predictions made, the highest accuracy for the combined least-squares method is for forecasting the groundwater fluctuations in the short-term. All the forecasts show a decrease in the groundwater fluctuations, indicating pumping wells around the Gohar Zamin Iron Ore Mine area.

The search for asbestos within the Peter Mitchell Taconite iron ore mine, near Babbitt, Minnesota

2008 ◽  
Vol 52 (1) ◽  
pp. S43-S50 ◽  
Author(s):  
Malcolm Ross ◽  
Robert P. Nolan ◽  
Gordon L. Nord
Keyword(s):  
Iron Ore ◽  
Iron Ore Mine ◽  
Peter Mitchell
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