Spatial Modelling of Lead (Pb) Concentration for the Soil in Sokoto Rima Basin, Using Co-Kriging
International Journal of Statistical Distributions and Applications
Volume 6, Issue 2, June 2020, Pages: 36-41
Received: Mar. 17, 2020; Accepted: Apr. 7, 2020; Published: Aug. 25, 2020
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Umar Usman, Department of Mathematics, Usmanu Danfodiyo University, Sokoto, Nigeria
Muddassiru Abubakar, Department of Mathematics, Federal University Birnin Kebbi, Kebbi, Nigeria
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This study used Geostatistics techniques to find the variability in the concentration of lead (Pb) in Sokoto Rima Basin Region. The concentrations Lead (Pb) were measured and analyzed in one hundred and three (103) different sample points in Sokoto Rima Basin region of Nigeria. The region is characterized as one of the center for agricultural activities in Nigeria. The soil samples were collected from agricultural, industrial and residential areas. The concentrations of heavy Lead (Pb) were measured using Atomic Absorption Spectrometer. The technique of Co-Kriging was used to develop empirical semivariogram model to predict the concentrations of Lead (Pb) in the soil. The result shows that concentrations of Lead (Pb) have exceeded the standard level in the study area. The study revealed that there are extreme concentrations of heavy metals in the central region of the study area.
Heavy Metal, Concentrations, Variogram, Co-Kriging
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Umar Usman, Muddassiru Abubakar, Spatial Modelling of Lead (Pb) Concentration for the Soil in Sokoto Rima Basin, Using Co-Kriging, International Journal of Statistical Distributions and Applications. Vol. 6, No. 2, 2020, pp. 36-41. doi: 10.11648/j.ijsd.20200602.12
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Fang X., Bifeng H., Shuai S., Dongyun X., Yue Z., Yin Z., Mingxiang H., Yan L., Songchao C. and Zhou S., (2019) “Improvement of spatial modelling of Cr, Pb, Cd, As and Ni in the soil based on portable X-ray fluorescence (PXRF) and Geostatistics” Journal of environmental research and public health., 16, 2694.
Gandhimathi, A., Meenambal, T., (2011). Spatial prediction of heavy metal pollution for soils in Coimbatore, India based on universal Kriging. International journal of computer applications 29 (10), 52-63.
Devkota, B., Schmidt, G. H., (2000). Accumulation of heavy metals in food plants and grasshopper from the Taigetos Mountain, Greece. Agriculture, ecosystems and environment, 78 (1), 85-91.
Frances S. F., Antonio M. G., Carmelo A. Z., Antonio G. S. and Pilar A. R., (2017). Spatial distribution of heavy metals and environmental quality of soil in the northern plateau of Spain by Geostatistical method. International journal of environmental research and public health. 14, 568.
Adejumo, J., Obioh, I., Ogunsola, O., Akeredolu, F., Olaniyi, H., Asubiojo, O., Oluwole, A., Akanle, O., and Spyrou, N., (1994). The atmospheric deposition of major, minor and trace element within and around cement factory. Journal of Radio Analytic and Nuclear Chemistry 179, 195-204.
Schuhmacher, M., Nadal, M., Domingo, J. L., (2009). Environmental monitoring of PCDD/Fs and metals in the vicinity of cement plant after using sewage sludge as secondary fuel. Chemosphere 74, 1502-1508.
CPCB (Central Pollution Control Board), (2007). Assessment of fugitive emission and development of environmental guidelines for control fugitive emission in cement manufacturing industries, programme objective series probes/118/2017, Delhi, India pp. 34-110.
Ogunkunle, C. O., Fatoba, P. O., (2014). Contamination and spatial distribution of heavy metals in topsoil surrounding a mega cement factory. Journal of atmospheric pollution research 5, 270-282.
Achternbosch, M., Brautigam, K. R., Herlieb, N., Kupsch, R., Richers, U., Stemmermann, P., (2003). Heavy metals in cement and concrete resulting from Co-incineration of waste in cement kilns with regard to the legitimacy of waste utilization, Mitglied der Hermann vonn Helmholtz-Gemeinschaft Deutscher Forschungszentren, ISSN 0947-8620, pp. 22-23.
Kataba P., A. Mukherjee, A. B., (2007). Trace element from soil to human, Springer verlag, Berlin, pp. 1-48.
Krige, D. G., (1951). A statistical approach to some basic mine valuation on the Witwatersrand. Journal of the Chemical, Metallurgical and Mining Society, 52: 119-139.
Matheron, G., (1963). Le Krigeage universal. Vol. 1. Cahiers du Centre de Morphologie Mathematique, Ecole des Mines de Paris, Fontainebleau, p. NA.
Webster, R., Oliver, M., (2001). Geostatistics for Environmental Scientists Statistics in Practice. Wiley, Chichester, 271pp.
David, M. (1977). Geostatistical Ore reserve estimation. Amsterdam: Elsevier.
Burrough, P., (1993). Soil Variability: a late 20th century view. Soils and Fertilizers, 56: 529 562.
Burgess, T. M., and Webster, R., (1980). Optimal interpolation and isarithmic mapping of soil properties: The semi-variogram and punctual kriging. Journal Soil Science., 31: 315-331.
Webster, R., (1994). The development of Pedometrics. Geoderma, 62: 1-15.
McGrath, D. and Zhang, C., (2003). Spatial distribution of soil organic carbon Concentrations in Grassland of Ireland. Applied Geochemistry, 18: 1629 1639.
Goovaerts, P., (1999). Geostatistics in soil science: state-of-the-art and perspectives. Geoderma, 89 (1-2): 1-45.
Webster, R. and Oliver, M. A., (2001). Geostatistics for Environmental Scientists. John Wiley and Sons Ltd, Chichester.
Goovaerts, P., (1997). Geostatistics for Natural Resource Evaluation, Oxford Univ. Press, New York.
Odeh, I. O. A., McBratney A. B. and Chittleborough, D. J., (1995). Further results on prediction of soil properties from terrain attributes: heterotopic cokriging and regression-kriging. Geoderma.
Mohamed S. S., Ahmed A. E., Michael A., Fullen, Talaat R. E., Ali R. R., A. Abd E., Antonio J. T. Guerra, Maria C. O. Jorge, (2016). Spatial distribution of heavy metals in the nile delta of Egypt. International soil and water conservation research 4, 293-303.
Wedepohl, K. H., (1995). The composition of the continental crust. Geochimica et Cosmochimica Acta, 59, 1217–1239.
Gandhimathi, A., Meenambal, T., (2012). Spatial prediction of heavy metal pollution for soils in Coimbatore, India based ANN and Kriging model. European scientific journal. June edition 8 (14), 79-91.
Usman U., S. A. Yelwa, S. U. Gulumbe, and A. Danbaba., (2013). “An Assessment of the Changing Climate in Northern Nigeria Using Cokriging.” American Journal of Applied Mathematics and Statistics 1, no. 5: 90-98. doi: 10.12691/ajams-1-5-3.
Yelwa, S. A. and, U. Usman, (2017). Integration of Spatial Prediction in the Assessment of Vegetation Productivity in the Northern Part of Nigeria. American Journal of Climate Change, 6, 360-373.
Abbas H., Norges S. and Ali G. (2014) “Spatial variability of heavy metals in the soil of Ahwaz using geostatistics method” International Journal of Environmental Science and Development, 5 (3), 294-298.
Asma, S. and Javel, I. (2018). “Spatial distribution and mobility assessment of carcinogenic heavy metals in the soil profile using geostatistics and random forest, Boruta algorithm” Sustainability, 10, 799.
Myers, D. E. (1982). Matrix Formulation of Cokriging, Mathematical Geology, (14) 3, pp. 249–257.
Isaaks, E. H. and Srivastava, R. M (1989). Applied Geostatistics, Oxford University Press, New York, 561 pp.
Wackernagel, H. Multivariate Geostatistics, Springer-Verlag, Berlin. (1995). 255 pp.
Wellmer, F. W (1998). Statistical Evaluations in Exploration for Mineral deposits, Springer-Verlag, Berlin. 379 pp.
Kalivas D. P., Triantakonstantis D. P. and Kollias V. J. (2002). "Spatial prediction of two soil properties using topographic information". Global Nest: The Int. Journal, 4 (1) 41-49.
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