Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.)

Environmental Pollution

Volumn 157, Issue 7, 2009, Pages 2061-2065

  Samecka Cymerman, A ^a   Stankiewicz, A ^a   Kolon, K ^a   Kempers, A J ^b  

^a UNIVERSITY OF WROC AW   (Poland)

^b RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

Bioindication; Heavy metal; Traffic pollution

Indexed keywords

BIOINDICATION; BIOINDICATOR; CONTROL SITES; MOTOR VEHICLES; POLLUTED SITES; ROAD TRAFFICS; ROBINIA PSEUDO ACACIAS; SELF-ORGANIZING FEATURE MAPS; TRAFFIC INTENSITIES; TRAFFIC POLLUTION;

AIR QUALITY; CHROMIUM; CONFORMAL MAPPING; LEAD; MANGANESE; MANGANESE COMPOUNDS; NEURAL NETWORKS; SOILS; ZINC;

SOIL POLLUTION;

BIOLOGICAL MARKER; CADMIUM; CHROMIUM; COPPER; LEAD; ZINC;

ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; BARK; BIOACCUMULATION; BIOINDICATOR; DECIDUOUS TREE; HEAVY METAL; LEAF; SELF ORGANIZATION; SOIL POLLUTION; TRAFFIC EMISSION;

AIR POLLUTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; BARK; ROBINIA; ROBINIA PSEUDOACACIA; SOIL ANALYSIS; SOIL POLLUTION; TRAFFIC;

CITIES; ENVIRONMENTAL MONITORING; ENVIRONMENTAL POLLUTION; METALS, HEAVY; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PLANT BARK; PLANT LEAVES; POLAND; ROBINIA; SEASONS; SOIL; VEHICLE EMISSIONS;

CENTRAL EUROPE; DOLNOSLASKIE; EURASIA; EUROPE; OLESNICA; POLAND;

ROBINIA PSEUDOACACIA;

EID: 65349125337     PISSN: 02697491     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envpol.2009.02.021     Document Type: Article

References (32)

1. Aksoy A., Sahin U., and Duman F. Robinia pseudo-acacia L. as a possible biomonitor of heavy metal pollution in Kayseri. Turk. J. Bot 24 (2000) 279-284
2. Baycu G., Tolunay D., Özden H., and Günebakan S. Ecophysiological and seasonal variations in Cd, Pb, Zn, and Ni concentrations in the leaves of urban deciduous trees in Istanbul. Environ. Pollut 143 (2006) 545-554
3. Bussotti F., Grossoni P., Batistoni P., Ferreti M., and Cenni E. Preliminary studies on the ability of plant barriers to capture lead and cadmium of vehicular origin. Aerobiologia 11 (1995) 11-18
4. Campo G., Orsi M., Badino G., Giacomelli R., and Spezzano P. Evaluation of motorway pollution in a mountain ecosystem. 1996. Pilot project: Susa Valley (Northwest Italy) years 1990-1994. Sci. Total Environ 189/190 (1996) 161-166
5. Čeburnis D., and Steinnes E. Conifer needles as biomonitors of atmospheric heavy metal deposition: comparison with mosses and precipitation role of the canopy. Atmos. Environ 34 (2000) 4265-4271
6. Çelik A., Aslihan A., Kartal A., Akdoǧan A., and Kaska Y. Determining the heavy metal pollution in Denizli (Turkey) by using Robinia pseudo-acacia L. Environ. Int 31 (2005) 105-112
7. Çinar T., and Elik A. Determination of heavy metals in bio-collectors as indicator of environmental pollution. Intern. J. Environ. Anal. Chem. 82 (2002) 321-327
8. Denier van der Gon H.A.C., Hulskotte J.H.J., Visschedijk A.J.H., and Schaap M. A revised estimate of copper emissions from road transport in UNECE Europe and its impact on predicted copper concentrations. Atmos. Environ 41 (2007) 8697-8710
9. Farmer A.M., Bates J.W., and Bell J.N.B. A comparison of methods for the measurement of bark pH. Lichenologist 22 (1990) 191-197
10. 10) and in leaves of Nerium oleander L. and Lantana camara L. Chemosphere 62 (2006) 1665-1672
11. Gałuszka A. The chemistry of soils, rocks and plant bioindicators in three ecosystems of the Holy Cross Mountains, Poland. Environ. Monit. Assess 110 (2005) 55-70
12. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning (1989), Addison-Wesley, Reading, MA
13. Harju L., Saarela K.E., Rajander J., Lill J.O., Lindroos A., and Heselius S.J. Environmental monitoring of trace elements in bark of Scots pine by thick-target PIXE. Nucl. Instrum. Meth. B 189 (2002) 163-167
14. Kabata-Pendias A. Trace metals in soils-a current issue in Poland. Acta Universitatis Wratislaviensis, 2317-Prace Botaniczne 79 (2001) 13-20
15. Kohonen T. Self-Organizing Maps (1995), Springer, Berlin, Heidelberg, New York
16. Kozlov M.V. Sources of variation in concentrations of nickel and copper in mountain birch foliage near a nickel-copper smelter at Monchegorsk, north-western Russia: results of long-term monitoring. Environ. Pollut 135 (2005) 91-99
17. Kozlov M.V., Haukioja E., Bakhtiarov A.V., Stroganov D.N., and Zimna S.N. Root versus canopy uptake of heavy metals by birch in an industrial polluted area: contrasting behaviour of nickel and copper. Environ. Pollut 107 (2000) 413-420
18. Kuik P., and Wolterbeek H.T. Factor analysis of atmospheric trace-element deposition data in the Netherlands obtained by moss monitoring. Water Air Soil Pollut 84 (1995) 323-346
19. Lin Z.Q., Schemenauer R.S., Schuepp P.H., Barthakur N.N., and Kennedy G.G. Airborne metal pollutants in high elevation forests of southern Quebec, Canada, and their likely source regions. Agr. Forest Meteorol 87 (1997) 41-54
20. Marguì E., Queralt I., Carvalho M.L., and Hidalgo M. Assessment of metal availability to vegetation (Betula pendula) in Pb-Zn ore concentrate residues with different features. Environ. Pollut 145 (2007) 179-184
21. Mertens J., Vervaeke P., De Schrijver A., and Luyssaert S. Metal uptake by young trees from dredged brackish sediment: limitations and possibilities for phytoextraction and phytostabilisation. Sci. Total Environ 326 (2004) 209-215
22. Oliva S.R., and Rautio P. Could ornamental plants serve as passive biomonitors in urban areas?. J. Atmos. Chem. 49 (2004) 137-138
23. Reimann C., Arnoldussen A., Finne T.E., Koller F., Nordgulen Ø., and Englmaler P. Element contents in mountain birch leaves, bark and wood under different anthropogenic and geogenic conditions. Appl. Geochem 22 (2007) 1549-1566
24. Schleppi P., Tobler L., Bucher J.B., and Wyttenbach A. Multivariate interpretation of the foliar chemical composition of Norway spruce (Picea abies). Plant Soil 219 (2000) 251-262
25. Schulz H., Popp P., Huhn G., Stark H.J., and Schuurmann G. Biomonitoring of airborne inorganic and organic pollutants by means of pine tree barks. I Temporal and spatial variations. Sci. Total Environ 232 (1999) 49-58
26. Sokal R.R., and Rohlf F.J. Biometry (2003), The Principles and Practice of Statistics in Biological Research, Freeman and Company
27. StatSoft, Inc. STATISTICA (data analysis software system), version 8.0 (2007). http://www.statsoft.com
28. Suzuki K. Characterisation of airborne particulates and associated trace metals deposited on tree bark by ICP-OES, ICP-MS, SEM-EDX and laser ablation ICP-MS. Atmos. Environ 40 (2006) 2626-2634
29. Takahashi M., Higaki A., Nohno M., Kamada M., Okamura Y., Matsui K., Kitani S., and Morikawa H. Differential assimilation of nitrogen dioxide by 70 taxa of roadside trees at an urban pollution level. Chemosphere 61 (2005) 633-639
30. Tomašević M., Vukmirović Z., Rajšić S., Tasić M., and Stevanović B. Characterization of trace metal particles deposited on some deciduous tree leaves in an urban area. Chemosphere 61 (2005) 753-760
31. Van Herk C.M. Bark pH and susceptibility to toxic air pollutants as independent causes of changes in epiphytic lichen composition in space and time. Lichenologist 33 (2001) 419-441
32. Zar H. Biostatistical Analysis (1999), Prentice Hall, Upper Saddle River, NJ