Abstract
The aim of this work was to provide information concerning the distribution of heavy metals in soils of a polluted ecosystem, in order to predict potential environmental risks and to provide a tool for the decision maker. This paper focuses on characterizing the industrial area of Tito (PZ, southern Italy), a site included among national interest sites to decontaminate, according to D.M. 8/7/2002. Soil contamination was monitored by means of a chemical-physical evaluation, coupled with a modelling approach using geostatistic techniques. A multistep sequential acid extraction technique was used to determine partitioning and levels of heavy metals in soil samples. Results showed that concentrations of analyzed elements are high in the whole area and above legislative admissible limits. A high spatial variation of heavy metals was observed in the studied area, with higher levels of heavy metals beside active and abandoned industrial areas. The adopted approach highlighted that anthropogenic industrial pressure may have detrimental repercussions on the surrounding environment and that recovering contaminated areas by implementing decontamination or permanent making safe interventions becomes necessary.
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References
Aboal, J.R., Real, C., Fernàndez, J.A., Carballeira, A.: Mapping the results of extensive surveys: The case of atmospheric biomonitoring and terrestrial mosses. Sci. Total Environ. 356, 256–274 (2006)
APAT–ISS Protocollo operativo per la determinazione dei valori di fondo di metalli/metalloidi nei suoli dei siti d’interesse nazionale, Roma, Italy (2006), www.apat.gov.it/site/_files/Suolo_Territorio/TEC_valori_di_fondo.pdf
Bailey, T.C.: A review of statistical spatial analysis in geographical information systems. In: Fotheringham, S., Rogerson, P. (eds.) Spatial analysis and GIS. Taylor & Francis, London (1994)
Bivand, R.S., Pebesma, E.J., Gómez-Rubio, V.: Applied spatial data analysis with R. Springer, Heidelberg (2008)
Bocchi, S., Castrignanò, A., Fornaro, F., Maggiore, T.: Application of factorial kriging for mapping soil varation at field scale. European Journal of Agronomy 13(4), 295–308 (2000)
Burrough, P.A.: GIS and Geostatistics: Essential partners for spatial analysis. Environmental and Ecological Statistics 8(4), 361–377 (2001)
Capri, E., Trevisan, M.: I metalli pesanti di origine agricola nei suoli e nelle acque sotterranee. Collana Quaderni di tecniche di protezione ambientale. sezione Protezione delle acque sotterranee. Pitagora Editrice, Bologna (2002)
Castrignanò, A., Maiorana, M., Fornaro, F., Lopez, N.: 3D spatial variability of soil strength and its change over time in a durum wheat field in Southern Italy. Soil & Tillage Research 65(1), 95–108 (2002)
Castrignanò, A., Stelluti, M.: Analisi delle caratteristiche fisico-chimiche dei suoli. In: Flagella, Z., Tarantino, E. (eds.) Caratterizzazione agroecologica del territorio garganico, Claudio Grenzi Editore, Foggia, Italy (2003)
Chiles, J.P., Delfiner, P.: Geostatistics modeling spatial uncertainty. John Wiley & Sons, Chichester (1999)
Cicchella, D., Albanese, S.: Cartografia geochimica con l’uso di sistemi informativi geografici (GIS). In: Lima, A., De Vivo, B., Siegel, F.R. (eds.) Geochimica ambientale, Liguori Editore, Napoli, Italy (2004)
Lgs, D.: 152/2006 (Decreto Legislativo 3/4/2006, n° 152) Norme in materia ambientale. Gazzetta Ufficiale Repubblica Italiana n. 88 del 14/04/2006 (S.O. n. 96)
D.M. 471/99 (Decreto Ministeriale 25/10/1999, n° 471) Regolamento recante criteri, procedure e modalita’ per la messa in sicurezza, la bonifica e il ripristino ambientale dei siti inquinati, ai sensi dell’articolo 17 del decreto legislativo 5/02/1997, n. 22, e successive modificazioni e integrazioni. Gazzetta Ufficiale Repubblica Italiana n. 293 del 15/12/1999 (S.O. n. 218)
El Sebai, T., Lagacherie, B., Soulas, G., Martin-Laurent, F.: Spatial variability of isoproturon mineralizing activity within an agricultural field: Geostatistical analysis of a simple physicochemical and microbiological soil parameters. Environ. Pollut. 145, 680–690 (2007)
EPA (Environmental Protection Agency) QA/G-9S, Data quality assessment: Statistical methods for practitioners. Office of Environmental Information, Washington, DC 20460, USA (2006)
Gupta, S.K., Vollmer, M.K., Krebs, R.: The importance of mobile, mobilisable and pseudo total heavy metal fractions in soil for three-level risk assessment and risk management. Sci. Total Environ. 178, 11–20 (1996)
Haining, R.: Spatial Data Analysis: Theory and Practice. Cambridge University Press, Cambridge (2003)
Hlavay, J., Prohaska, T., Weisz, M., Wenzeland, W.W., Stingeder, G.J.: Determination of Trace Elements Bound to Soils and Sediment Fractions. Pure Appl. Chem. 76, 415–422 (2004)
Iacus, S., Masarotto, G.: Laboratorio di statistica con R. McGraw-Hill, New York (2003)
Ihaka, R., Gentleman, R.: R: A language for data analysis and graphics. Journal of computational and Graphical Statistics 5(3), 299–314 (1996)
Journel, A.G., Huijbregts, C.J.: Mining geostatistics. Academic Press, London (1978)
Leita, L., Petruzzelli, G.: Metalli pesanti. In: Violante, P. (ed.) Metodi di Analisi Chimica del Suolo. Cap XI. Collana di metodi analitici per l’agricoltura. Franco Angeli, Milano (2000)
Liang, Y., Wong, M.H.: Spatial and temporal organic and heavy metal pollution at Mai Po Marshes Nature Reserve, Hong Kong. Chemosphere 52, 1647–1658 (2003)
Lima, A., De Vivo, B., Siegel, F.R.: Geochimica ambientale. Liguori Editore, Napoli, Italy (2004)
Link, D.L., Kingstron, H.M.: Use of microwave assisted evaporation for the complete recovery of volatile species of inorganic trace analytes. Anal. Chem. 72(13), 2908–2913 (2000)
Liu, X., Wu, J., Xu, J.: Characterizing the risk assessment of heavy metals and sampling uncertainty analysis in paddy field by geostatistics and GIS. Environ. Pollut. 141, 257–264 (2006)
Lloyd, C.D., Lloyd, L.D.: Local Models for Spatial Analysis. CRC Press, Boca Raton (2006)
Madeo S., Penati, M.: Ricostruzione di campi di concentrazione di inquinanti sulla regione Lombardia mediante interpolatori geostatistici. Tesi di laurea, Politecnico di Milano (2005), http://www.mate.polimi.it/biblioteca/tesiview.php?id=11&L=i
Matheron, G.: Les variables regionalisees et leur estimation: une application de la théorie des fonctions aléatoires aux sciences de la nature. Masson, Paris (1965)
R Development Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2006), ISBN 3-900051-07-0, http://www.R-project.org
Reimann, C., Filzmoser, P., Garrett, R., Dutter, R.: Statistical Data Analysis Explained: Applied Environmental Statistics with R. John Wiley & Sons, Chichester (2008)
Ribeiro Jr., P.J., Brown, P.E.: Some words on the R project. The ISBA Bulletin 8(1), 12–16 (2001a)
Ribeiro Jr., P.J., Diggle, P.J.: geoR: A package for geostatistical analysis. R-NEWS 1(2), 15–18 (2001b), ISSN 1609-3631
Rodríguez, J.A., Nanos, N., Grau, J.M., Gil, L., López-Arias, M.: Multiscale analysis of heavy metal contents in Spanish agricultural topsoils. Chemosphere 70, 1085–1096 (2008)
Tessier, A., Campbell, P.G.C., Misson, M.: Sequential extraction procedure for the speciation of particulate trace metals. Anal. Chem. 51(7), 844–850 (1979)
Wu, C., Wu, J., Luo, Y., Zhang, H., Teng, Y.: Statistical and geostatistical characterization of heavy metal concentrations in a contaminated area taking account soil map units. Geoderma 144, 171–179 (2008)
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Lucia, P., Palma, A., Murgante, B., D’Alessandro, C.M., Sofo, A., Scopa, A. (2011). Using Environmental Geostatistics for the Geochemical Characterization of Soils from the Polluted Site of National Interest of Tito (PZ – Italy). In: Murgante, B., Borruso, G., Lapucci, A. (eds) Geocomputation, Sustainability and Environmental Planning. Studies in Computational Intelligence, vol 348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19733-8_8
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DOI: https://doi.org/10.1007/978-3-642-19733-8_8
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