Seasonal and spatial variability of 210Po, 238U and 239+240Pu levels in the river catchment area assessed by application of neural-network based classification

Journal of Environmental Radioactivity

Volumn 100, Issue 2, 2009, Pages 167-175

  Skwarzec, Bogdan ^a   Kabat, Krzysztof ^a   Astel, Aleksander ^b  

^a UNIVERSITY OF GDA SK   (Poland)

^b POMERANIAN MEDICAL UNIVERSITY   (Poland)

Author keywords

Classification; Environmetrics; Radionuclides; Self organizing map; Vistula river (Poland, southern Baltic)

Indexed keywords

CLASSIFICATION; ENVIRONMETRICS; RADIONUCLIDES; SELF-ORGANIZING MAP; VISTULA RIVER (POLAND, SOUTHERN BALTIC);

CATCHMENTS; CONFORMAL MAPPING; DATA VISUALIZATION; PLUTONIUM; RADIOISOTOPES; RADIOMETRY; RUNOFF; SELF ORGANIZING MAPS; SPRINGS (COMPONENTS); STRENGTH OF MATERIALS;

RIVERS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; CATCHMENT; CLASSIFICATION; DATA SET; HUMAN ACTIVITY; OPTIMIZATION; PLUTONIUM ISOTOPE; POLONIUM ISOTOPE; RADIOACTIVE POLLUTION; RADIONUCLIDE; RIVER POLLUTION; SPATIOTEMPORAL ANALYSIS; URANIUM ISOTOPE; VISUALIZATION;

ENVIRONMENTAL MONITORING; PLUTONIUM; POLAND; POLONIUM; RIVERS; SEASONS; URANIUM; WATER POLLUTANTS, RADIOACTIVE;

ATLANTIC OCEAN; BALTIC SEA; CENTRAL EUROPE; EURASIA; EUROPE; POLAND; VISTULA RIVER;

EID: 58249091386     PISSN: 0265931X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jenvrad.2008.11.007     Document Type: Article

References (75)

1. Aarkrog A. The radiological impact of the Chernobyl debris compared with that from weapons fallout. J. Environ. Radioact. 6 (1988) 151-162
2. Alp M., and Cigizoglu H.K. Suspended sediment load simulation by two artificial neural network methods using hydrometeorological data. Environ. Modell. Softw. 22 (2007) 2-13
3. Alvarez-Guerra M., Gonzáles-Pinuela C., Andrés A., Galán B., and Viguri J.R. Assessment of self-organizing map artificial neural networks for the classification of sediment quality. Environ. Int. (2008) 10.1016/j/envint.2008.01.006
4. Arsuage U.A., and Díaz M.F. Topology preservation in SOM. Proceedings of World Academy of Science, Engineering and Technology 16 (2006) 187-190
5. Astel A., Boszke L., Niedzielski P., and Kozak L. Application of the self-organizing mapping in exploration of the environmental impact of tsunami disaster. J. Environ. Sci. Health, Part A 43 9 (2008) 1016-1025
6. Astel A., and Małek S. Multivariate modeling and classification of environmental n-way data from bulk precipitation quality control. J. Chemom. 21 (2008) 1-9
7. Astel A., Tsakovski S., Barbieri P., and Simeonov V. Comparison of self-organizing maps classification approach with cluster and principal components analysis for large environmental data sets. Water Res. 41 (2007) 4566-4578
8. Astel A., Tsakovski S., Simeonov V., Reisenhofer E., Piselli S., and Barbieri P. Multivariate classification and modeling in surface water pollution estimation. Anal. Bioanal. Chem. 390 5 (2008) 1283-1292
9. Bolivar J.P., Garcia-Tenerio R., and Vaca F. Radioecological Study of an Estuarine System Located in the South of Spain (2000), Elsevier Science, Great Britain
10. Boszke L., and Astel A. Application of neural network-based modeling in assessment of mercury pollution level in the middle part of the Warta River. Environ. Monit. Assess. (2008) 10.1007/s10661-008-0302-x
11. 210Po in the Tagues estuary, Portugal. Sci. Total Environ. 191 (1997) 151-161
12. Céréghino R., Giraudel J.L., and Compin A. Spatial analysis of stream invertebrates distribution in the Adour-Garonne drainage basin (France) using Kohonen self-organizing maps. Ecol. Model. 146 (2001) 167-180
13. Cottrell M., Fort J.C., and Pagès G. Theoretical aspects of the SOM algorithm. Neurocomputing 21 (1998) 119-138
14. Coughtrey P.J., Jackson D., Jones C.H., Kane P., and Thorne M.C. Radionuclide Distribution and Transport Terrestrial and Aquatic Ecosystems: A Critical Review of Data (1984), A.A. Balkema, Rotterdam
15. Cun C., and Vilagines R. Time series analysis of chloride, nitrates, ammonium and dissolved oxygen concentration in the Seine river rear Paris. Sci. Total Environ. 208 1-2 (1997) 59-69
16. Danielsen E.F. Trajectories of the Mount St. Helens plume. Science 211 (1981) 819-821
17. Davies D.L., and Bouldin D.W. A cluster separation measure. Proceeding of the IEEE Transactions on Pattern Recognition and Machine Intelligence 1 2 (1979) 224-227
18. Ehsani A.H., and Quiel F. Application of Self-Organizing Map and SRTM data to characterize yardangs in the Lut desert, Iran. Remote Sens. Environ. 112 7 (2008) 3284-3294
19. Eyrolle F., Charmasson S., and Louvat D. Plutonium isotopes in the lower reaches of the River Rhone over the period 1945-2000; fluxes towards the Mediterranean Sea and sedimentary inventories. J. Environ. Radioact. 74 (2004) 127-138
20. Flues M., Morales V., and Mazzilli B.P. The influence of a coal-fired plant operation on radionuclides in soil. J. Environ. Radioact. 63 (2002) 285-294
21. Fort J.C. SOM's mathematics. Neural Net. 19 (2006) 812-816
22. Giraudel J.L., and Lek S. A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination. Ecol. Model. 146 (2001) 329-339
23. Gulson B., Korsch M., Dickson B., Cohen D., Mizon K., and Davis M.J. Comparison of lead isotopes with source apportionment models, including SOM, for air particulates. Sci. Total Environ. 381 (2007) 169-179
24. Hardy E.P., Krey P.W., and Volchok H.L. Global inventory and distribution of fallout plutonium. Nature 241 (1973) 444-445
25. Haridasan P.P., Paul A.C., and Desai M.V.M. Natural radionuclides in the aquatic environment of a phosphogypsum disposal area. J. Environ. Radioact. 53 (2001) 155-165
26. Hewitson B.C., and Crane R.G. Self-organizing maps: applications to synoptic climatology. Clim. Res. 22 (2002) 13-26
27. Jahnz, A., 2007, Polonium, uranium and plutonium run-off in Vistula river basin, Ph.D. Thesis, Gdańsk University, Faculty of Chemistry, Gdańsk.
28. Jaworowski Z. Radioactive lead in the environment and human body. At. Energy Rev. 7 (1969) 3-45
29. Jaworowski Z., and Kownacka L. Lead and radium in the lower stratosphere. Nature 263 (1976) 303-304
30. Kalteh A.M., Hjorth P., and Berndtsson R. Review of the self-organizing map (SOM) approach in water resources: analysis, modeling and application. Environ. Modell. Softw. 23 (2008) 835-845
31. Kohonen T. Self-organizing formation of topologically correct feature maps. Biol. Cybern. 43 (1982) 59-69
32. Kohonen T. Self-Organization and Associative Memory (1984), Springer Verlag, Berlin, Germany
33. Kohonen T. Self-Organizing Maps (1995), Springer, New York
34. Kohonen T., Oja E., Simula O., Visa A., and Kangas J. Engineering applications of the self-organizing map. Proceeding of the IEEE 84 (1996) 1358-1384
35. Kohonen T. Self-Organizing Maps. third ed. (2001), Springer, Berlin, Germany
36. Ku T.L., Knauss K.G., and Mathieu G.G. Uranium in open ocean: concentration and isotopic composition. Deep-Sea Res. 24 (1977) 1005-1017
37. Lacassie J.B., Roser B., Del Solar J.R., and Hervé F. Discovering geochemical patterns using self-organizing neural networks: a new perspective for sedimentary provenance analysis. Sediment. Geol. 165 (2004) 175-191
38. Langmuir D. Uranium solution - mineral equilibria at low temperature with applications to sedimentary are deposits. Geochim. Cosmochim. Acta 42 (1978) 547-569
39. Lambert G., Buisson A., Sanak J., and Ardouin B. Modification of the atmospheric polonium-210 to lead-210 ratio by volcanic emissions. J. Geophys. Res. 84 (1979) 6980-6986
40. Lee B.H., and Scholz M. Application of the self-organizing maps (SOM) to assess the heavy metal removal performance in experimental constructed wetlands. Water Res. 40 18 (2006) 3367-3374
41. Lek S., and Guégan J.F. Artificial neural networks as a tool in ecological modeling, an introduction. Ecol. Model. 120 (1999) 65-73
42. Makinia J., Dunnette D., and Kowalik P. Water pollution in Poland. Eur. Water Pollut. Control 6 2 (1996) 26-33
43. Mangiameli P., Chen S.K., and West D. A comparison of SOM neural network and hierarchical clustering methods. Eur. J. Oper. Res. 93 (1996) 402-417
44. Massart D.L., and Kaufman L. In: Kaufman L. (Ed). The Interpretation of Analytical Chemistry Data by the Use of Cluster Analysis (1983), John Wiley and Sons, New York 45-55
45. McDonald P., Fowler S.W., Heyraud M.W., and Baxter M.S. Polonium-210 in mussels and its implications for environmental alpha-autoradiography. J. Environ. Radioact. 3 (1986) 293-303
46. Miller A.C., Blakely W.F., Livengood V., Whittaker T., Xu J., Ejnik W.J., Hamilton M.M., Parlette E., John T.S., Gerstenberg H.M., and Hsu H. Transformation of human osteoblast to tumorigenic phenotype by depleted uranium-uranyl chloride. Environ. Health Perspect. 106 (1998) 465-471
47. Mingoti S.A., and Lima J.O. Comparing SOM neural network with Fuzzy c-means, k-means and traditional hierarchical clustering algorithms. Eur. J. Oper. Res. 174 (2006) 1742-1759
48. Moore H.E., Martell E.A., and Poet S.E. Source of polonium-210 in the atmosphere. Environ. Sci. Technol. 10 (1976) 586-591
49. Moshou D., Bravo C., Oberti R., West J., Bodria L., McCarney A., and Ramon H. Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps. Real-Time Imaging 11 2 (2005) 75-83
50. MSO (Major Statistical Office), 2005a. Environment Protection. Data and statistical assessment, Warsaw.
51. MSO (Major Statistical Office), 2005b. Land use, crops surface, livestock population in 2005. Data and statistical assessment, Warsaw.
52. Mukherjee A. Self-organizing neural network for identification of natural modes. J. Comput. Civil Eng. 11 1 (1997) 74-77
53. Othman L., and Yassine T. Natural radioactivity of drinking water in the southern and middle parts of Syria. Environ. Int. 22 1 (1996) 355-359
54. Patočka J., Kassa J., Štětina R., Šafr G., and Havel J. Toxicological aspects of depleted uranium. J. Appl. Biomed. 2 (2004) 37-42
55. Park Y.S., Céréghino R., Compin A., and Lek S. Application of artificial neural networks for patterning and predicting aquatic insect species richness in running waters. Ecol. Model. 160 (2003) 265-280
56. Peeters L., Bação F., Lobo V., and Dassargues A. Exploratory data analysis and clustering of multivariate spatial hydrogeological data by means of GEO3DSOM, a variant of Kohonen's Self-Organizing Map. Hydrol. Earth Syst. Sci. Discuss. 3 (2006) 1487-1516
57. Recknagel, F., 2003, Ecological Informatics: Understanding Ecology by Biologically Inspired Computation, Springer, Germany, Berlin.
58. Richardson A.J., Risien C., and Shillington F.A. Using self-organizing maps to identify patterns in satellite imagery. Prog. Oceanogr. 59 (2003) 223-239
59. 238U ratios. J. Radioanal. Nucl. Chem. 190 1 (1995) 113-120
60. Shaheed K., Somasundaram S.S.N., Hameed P.S., and Iyengar M.A.R. A study of polonium-210 distribution aspects in the riverine ecosystem of Kaveri Tiruchirappalli, India. Environ. Pollut. 95 3 (1997) 371-377
61. Simeonov V., Einax J.W., Stanimirova I., and Kraft I. Environmetric modeling and interpretation of river water monitoring data. Anal. Bioanal. Chem. 374 (2002) 898-905
62. Simeonov V., Sarbu C., Massart D.L., and Tsakovski S. Dunabe river water data modeling by multivariate data analysis. Microchim. Acta 137 3-4 (2001) 243-248
63. Skwarzec, B., 1995. Polonium, uranium and plutonium in the southern Baltic ecosystem. Thesis and monographies, Institute of Oceanology PAN, 6, Sopot.
64. Skwarzec B. Radiochemical methods for the determination of polonium, radiolead, uranium and plutonium in environmental samples. Chem. Anal. 42 (1997) 107-115
65. 238U isotopes in southern Baltic. Water, Air, Soil Pollut. 159 (2004) 165-173
66. 210Po from Vistula river catchments area. J. Environ. Sci. Health A 42 (2007) 1-6
67. 239Pu atomic ratios in Baltic Sea ecosystem, Int. J. Environ. Anal. Chem.
68. 210Pb in the water column at Kuala Selangor, Malaysia. J. Environ. Radioact. 80 (2005) 273-286
69. Tutu H., Cukrowska E.M., Dohnal V., and Havel J. Application of artificial neural networks for classification of uranium distribution in the Central Rand goldfield, South Africa. Environ. Model. Assess. 10 (2005) 43-152
70. Ultsch, A., Siemon, H.P., 1990. Kohonen's self-organizing feature maps for exploratory data analysis. In: Proceedings of International Neural Network Conference (INNC'90). Kluwer, Dordrecht, Netherlands, pp. 305-308.
71. 226Ra in surface waters from a river passing through a granitic region in the southwest of Spain. Nucl. Geophys. 9 6 (1995) 567-578
72. Vesanto, J., 2000. Neural network tool data mining: SOM Toolbox. Proceedings of Symposium on Tool Environments and Development Methods for Intelligent Systems (TOOL-MET2000), Oulun yliopistopaino, Finland, Oulu, pp. 184-196.
73. Vesanto, J., Himberg, J., Alhoniemi, E., Parhankagas, J., 2000, SOM Toolbox for Matlab 5, Report A57, (visited 15.02.2007, ).
74. Vukovich F.M., Gilliand A., Venkatram A., and Sherwell J. On performing long-term predictions of ozone using the SOMs model. Atmos. Environ. 35 (2001) 569-578
75. Walley W.J., Martin R.W., and O'Connor M.A. Self-Organizing Maps for Classification of River Quality from Biological and Environmental Data. Hardbound. In: Denzer R., Swayne D.A., Purvis M., and Schimak G. (Eds). Environmental Software Systems: Environmental Information and Decision Support, IFIP Conference Series (2000), Kluwer Academic Publishers, Boston 27-41