FATE OF TRACE ELEMENTS IN THE VENICE LAGOON WATERSHED
AND CONTERMINOUS AREAS (ITALY)

C. Bini

Dept. of Environmental Sciences, University of Venice - Dorsoduro, 2137.30123- Venezia, Italy.
 E-mail: bini@unive.it

Abstract. Element mobility is of major importance with regard to bioavailability and the potential risk for contamination. Different factors control the ultimate fate of a toxic element in the environment, that is, if it will precipitate or will be adsorbed , or  released, transported and taken up by organisms.
The objectives  of this work are:
•	To evaluate background levels of heavy metals in soils of highly vulnerable area in northern Italy. 
•	To ascertain metal mobility and possible contamination of some sites, and the related environmental hazard, with special reference to the pollution of the Venice lagoon, which is a unique and delicate ecosystem.
The Venetian territory is characterized by different pedolandscapes:
•	A wide plain formed by alluvial deposits. Most soils here (Entisols, Inceptisols, Alfisols) are cultivated with extensive agriculture;
•	Gently ondulating conglomerates, marls and limestones with shallow soils (Entisols and Inceptisols) frequently cultivated with vineyards, or forested;
•	Mountain ranges with steep morphology. Forestry and grassland are the main land utilization types on these soils (mostly Inceptisols and Mollisols).

Approximately 900 soil samples from 300 representative soil profiles were analyzed for As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb,  Zn. Data were statistically processed to find close relationships among elements. 
Agriculture soils. The soils examined (more than 200 sites) contain generally high levels of anthropogenic Cu, Zn, Pb, and As.
Forest soils. The heavy metal contents in the soils examined (more than 100 sites) are generally below the target values and depend mainly upon local physico-chemical and geological conditions. Anthropogenic Pb and Cd  are concentrated especially in organic layers.

Increasing acidic conditions, redox status, organic matter content and pore solution are the factors responsible for trace elements mobilization within the soil. From the soil, trace elements move to groundwater and to lagoon, where they are concentrated in sediments or transferred to organisms.
 The elements with the lowest relative mobility (bioavailability) are Co, Cr, Hg, Pb, As; intermediate elements are Cu, Ni and the most bioavailable are Zn and Cd.
The soils investigated have heavy metal concentrations that are generally within the regulatory guidelines. Exceptions are  anthropogenic Cu and Zn in agricultural soils, Cd and Pb at forest sites.
The ecological risk posed by single elements is limited for As and very high for Cd. The cumulative toxic risk indicates a relevant bioaccumulation of trace elements in the lagoon ecosystem.

Key words: soil contamination; Venice Lagoon watershed; environmental pollution; environmental hazard; pedometrics.

1.	Introduction.
Research on distribution and circulation of trace elements in different environmental contexts, since the last decades, has received a remarkable attention from various scientific domains (e.g. geology, pedology, chemistry, agronomy, botany, pharmacy). The increasing interest concerned particularly the following topics:
- background knowledge and soil genesis;
- environmental contamination;
- groundwater pollution;
- soil remediation;
- toxicology and human health.

The results achieved in these different items allow a general insight on the distribution and circulation of trace elements in natural environments, though quantitative estimation of elemental fluxes and resident time in the different geochemical spheres, especially the pedosphere, is still deficient. As a matter of fact, present knowledge not only does not permit to have reliable data on the levels of some soil microelements (e.g. As, Cd, Cr, Hg, Tl), but also it does not highlight the main processes which control kinetics, equilibria, circulation and fluxes of elements in the environment.
Element mobility in the exogenic environment is of major importance with regard to their bioavailability and the potential risk for contamination. Indeed, supergenic alteration processes may lead to the release of potentially toxic elements, particularly heavy metals, in the environment. The factors that control the ultimate fate of a toxic element, that is, if it will precipitate as an insoluble phase or will be adsorbed on the surface of some other phase, or will be released, transported and eventually taken up by plants, depend mainly upon local physico-chemical, climatic, biologic and geologic conditions (Brummer, 1986; Langmuir, 1997).
In order to examine the behaviour of such elements, it is necessary to study the interface between rocks, the biosphere and the hydrosphere, that is, the pedosphere. This is a multicomponent complex system whose chemical equilibria are frequently in a thermodynamic steady state (Sposito, 1983). The rate of redox reactions, for example, may be influenced by mic roorganisms. Reduced or oxidized elements may, in turn,  influence the geochemical behaviour of other elements (Cambier and Charlatchka, 1999).

Concerning heavy metals, these are "dispersed" trace elements with generally limited concentrations in the earth's crust and the related soils (Kabata Pendias and Pendias, 1992). However, metal accumulation in the environment may occur at some locations, owing to different sources (Angelone & Bini, 1992). Possible "natural' accumulation may be related to heavy metal-bearing rocks (e.g. Ni and Cr in serpentine: Angelone et al., 1993) or to mineralized areas (e.g. Pb and Zn from mixed sulfide mines: Benvenuti et al., 1997), while anthropogenic accumulation is related to industrial activities (e.g. Cd in metallurgy, Cr in varnish and leather factories: Bini et al., 2008), agriculture and urban sewage sludge (e.g. Zn and Cu from fertilizers: Deluisa et al., 1996; Cd, Pb, Cr from sludge: Petruzzelli, 1989).

Especially the last item is paying great attention at present, since increasing quantities of urban sludge are produced and extensively introduced in the environment. Moreover, atmospheric input from industrial emissions, heat power plants, heavy traffic and acid rains may account for increasing heavy metal concentration in soils (Norra et al., 2006). Therefore, identification of the sources responsible for soil contamination is an important issue, since high loads of heavy metals applied to soils, or stored in soils, may determine soil quality degradation, surface and groundwater pollution, accumulation in plants, phytotoxicity and successive transfer to the food chain.
All trace elements are toxic if their intake through ingestion or inhalation is excessive. In particular Ag, As, Be, Cd, Ce, Ge, Hg, Pb, Tl are good examples of potentially harmful elements (PHEs) that have no proven essential functions, and are known to have adverse physiological effects at relatively low concentrations (Abrahams, 2002).
Examples of toxicity by heavy metals are known since the Antiquity (Nriagu, 1983). For instance, one of the supposed causes for the Roman Empire drop is the increasing lead toxicity from Pb-bearing potteries and wine containers, as it was found in Roman findings and bones. Lead (saturnism) and Hg (hydrargillism) poisoning cases were frequently recorded in workers employed in mining industry and even in hat factories in Tuscany (Dall’Aglio et al., 1966). At present, diseases and toxicity related to microelement contamination (Cr, Cu, Ni, Pb, Tl, Zn,) of air, water and soil from industrial activities are well established (Thornton, 1993; Abrahams, 2002). For example, the most notable cause of Tl poisoning occurred adjacent to a cement works in Germany (Abrahams, 2002).

The risk arising from metals depends on their bioavailability, which in turn depends in the form in which they occur (Adriano et al., 1995): this is the reason why the risk to human health cannot be assessed on the basis of the total concentration of the toxic metal. Background values correspond to the total content of metals in soils not affected by human activities, i.e. they are the reference values for most countries. Soil guide values have been  introduced in the late1950s in Japan, in 1980 in The Netherlands, in 1986 in Switzerland, in 1987 in Great Britain, in 1994 in Germany. Since that time, many countries, notably the U.S.A., Canada, Great Britain and the Netherlands, have progressed further in setting standards for hazardous constituents in soil, health-risk based soil screening levels and soil remediation. However, legislation on maximum admissible levels of heavy metals in the environment in the EU is rather confusing. Indeed, a general regulatory guideline on the maximum trace element concentration in soils has not yet been established, the current references being related to the total metal content in waste and sewage sludge to be spread on soil (Adriano et al., 1995). Moreover, there is little agreement among the members in their implementation of the EC Directive of 1986. Several attempts have been made to adopt background values in order to obtain more viable reference values for regulatory decision. Although there are some similarities, standard criteria on the background level of metals in soils, however, are not yet established. In many EU countries, the target values proposed by the Dutch Ministry of Housing, Spatial Planning and Environment (Table 1) have been accepted as the reference national values, although the strict application of the Dutch target values is difficult to achieve for several reasons (parameters influencing the bioavailability of metals, site-specific conditions, the use of land after restoration, etc).
 
Table 1. Dutch  target values (also referred to as A-value or reference value of the prior regulatory guidelines) and intervention values (also referred to as C-value) for selected metals in soil (mg/kg dry matter). (Source: Dutch Ministry of Housing, Spatial Planning and Environment. The Hague, The Netherlands)
            
Metal	target value                    	intervention value	
Arsenic	 29	 55 	
Barium 	200 	625 	
Cadmium	 0.8	 12 	
Chromium 	100 	380 	
Cobalt	  20 	240 	
Copper	  36 	190 	
Mercury	 0.3	  10 	
Lead	  85 	530 	
Molybdenum	  10 	200 	
Nickel	  35 	210 	
Zinc 	140 	720 	

The present values, although related to the total metal concentration, are based not only on considerations of the natural contaminant concentration, but also take into account the local circumstances. Moreover, they are regarded as having been exceeded, and the soil seriously contaminated. Furthermore, they take into account both human toxicological and ecotoxicological considerations (Adriano et al., 1995). 

Recent legislative regulations in EU were devoted to polluted sites reclamation, with particular reference to different land use. The Legislation Act 471/99, promoted by the Italian Ministry of Environment, deals with contaminated site restoration and soil protection, and introduces regulatory thresholds (Table 2), which, when exceeded, would require mandatory clean-up operations.

Table 2. Maximum metal concentration values recordable in soil and subsoil of contaminated sites, with reference to specific land utilization (L. A. n° 471/99, annexe 1).

	Green and residential areas	Commercial and industrial  areas	
	mg/kg d.m.	mg/kg d.m.	
Antimony	10	30	
Arsenic	20	50	
Berillium	2	10	
Cadmium	2	15	
Cobalt	20	250	
Chromium (total)	150	800	
Chromium VI	2	15	
Mercury	1	5	
Nickel	120	500	
Lead	100	1000	
Copper	120	600	
Selenium	3	15	
Tin	1	350	
Thallium	1	10	
Vanadium	90	250	
Zinc	150	1500	
Cianides	1	100	
Fluorides	100	2000	

Soil contaminants constitute a known global problem, and more knowledge is required of them, their behaviour, and their pathways to humans. Nevertheless, information on the chemical status of the elements is difficult to achieve.
Though in most cases reference is made to their total level in the different compartments, the fate of heavy metals in the environment depends upon their available fraction. Whilst soils may contain high total concentrations of elements, many factors, including soil pH and redox potential, clay and organic matter content, influence the speciation, mobility and bioavailability of elements to plants. The implication is that there are often a number of effective barriers operative in the transfer of potentially harmful elements from soils to food. 
Metal concentration generally is not directly related to the potential hazard: indeed, not all the metal present in the soil is available to plants, part of it being trapped in the crystal lattice of minerals (e.g. Ni in serpentine soils may achieve 800 mg/kg, but most of it is unavailable and therefore does not contribute to Ni toxicity). The bioavailability, however, is related to the chemical bonding of the metal with the soil mineral, the inorganic and organic colloids, the kind of humic substances, the physico-chemical conditions, etc. Sequential extraction, therefore, is needed to separate different fractions of heavy metals, in order to evaluate the actual environmental hazard of the different elements. Analytical protocols have already been established for this purposes, though doubts remain on the real efficiency and significance of different extractions.

Several  extractants have been indicated in the literature in order to obtain fractionation and speciation of the different forms of metal (see f.i. Tessier et al., 1979). Among them, EDTA or DTPA has been suggested by several authors (e.g. Goupta et al., 1994) as he most significant to evaluate the metal fraction potentially available to plants over a long period of time, while electrolytes like CaCl2  or NH4COOCH3  are considered to extract soluble and extractable fractions over a short time. 

A profound insight of the above mentioned items, therefore, is needed, in order to achieve the following finalisations:

a)	knowledge on the distribution and circulation of trace elements in the different geochemical domains (lithosphere, pedosphere, hydrosphere, biosphere, atmosphere) contributes to better understand the natural processes responsible for the soil genesis and evolution, the relations with landscape and vegetation, and the ecosystems equilibria;

b)	human activities, technological processes and modern industrial products pose major environmental pollution concerns. Water, soil, vegetation may be appreciably affected by toxic or critical substances emitted in the atmosphere, or introduced in surface and groundwater, by these activities. Successively, after a variable time interval, they may be deposited at the earth surface, posing environmental hazard. Potentially harmful elements  (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn, etc.) may have toxic effects on living organisms, including humans;
c)	Research on living organisms occurring at sites naturally and/or anthropically contaminated may allow identification of individuals (plants and animals), that are indicators of degraded environmental systems, or that may be utilized for restoration of contaminated sites, e.g. with phytoremediation techniques.

Based on the above mentioned assumptions, in the frame of soil surveys carried out in recent years (1997-2003) by the EPA of the Veneto Region and the University of Venice ( see f.i. Giandon et al., 2000; Bini and Zilocchi, 2001; Giandon et al., 2001) as a part of the intervention programs against pollution of the lagoon of Venice,  a survey of agricultural, industrial and undisturbed (forest, grassland and wetland) areas, including the lagoon, was carried out in the Venice drainage basin and the conterminous territory. 
The Lagoon of Venice  is a shallow transitional environment located in a densely populated industrial/agricultural area (population 1,500,000), in the northern part of the Adriatic sea (Fig. 1), from which it is separated by some flat and narrow islands. Three inlets allow water exchange between the lagoon and the Adriatic sea. The whole area of the lagoon and the conterminous land has historically undergone severe anthropogenic pressure, with direct inputs of pollutants from both industrial and urban discharges. Other sources of contamination are river inputs, which collect industrial, domestic and agricultural polluting substances coming from the drainage basin of the lagoon.

The objectives of this work were:
•	To evaluate the background level of heavy metals in soils of the Venice drainage basin and conterminous areas;
•	To estimate the environmental impact of agricultural and industrial activity; 
•	To ascertain metal mobility and possible contamination of some sites, and the related environmental hazard, with special reference to the pollution of the Venice lagoon, which is a unique and delicate ecosystem.

2. Materials and Methods.

2.1 Study area
The investigated territory extends for approximately 2000 km2, from the pre-Alpine fringe to the lagoon of Venice (Fig. 1, inset), and is characterized by different pedolandscapes (Giandon et al., 2001):
•	mountain ranges with steep morphology. The geology of this area is different from place to place, but limestone and dolostone dominate over crystalline or silicate rocks. Forestry and grassland are the main land utilisation types on these mountain soils (mostly inceptisols and mollisols);
•	gently ondulating conglomerates, marls and volcanic rocks of tertiary age, with shallow hills frequently cultivated with vineyards, or forested when slope gradient is high;
•	a wide alluvial plain originated by the sedimentary activity of alpine rivers during the Quaternary. It consists of alluvial deposits of mixed lithology (depending on erosional contribution from uplands), size and age. Most soils are cultivated with extensive agriculture. 
•	The south-eastern margins of the mainland are characterized by sand dunes, urban soils and reclaimed land with variable texture (from coarse-grained to fine-grained) and composition,  which form the borderline of the lagoon. 

The soil reference system is based on the typological approach adopted by EPA-Veneto (ARPAV, 2005), and focuses on both land characteristics, soil morphology and land use. Urban and undisturbed soils under annual crops, permanent grassland and forests were selected.
In the alluvial plain, which is part of the Soil Region 18.8 (Cambisols-Luvisols Region), the surveyed soils are characterized by a high degree of heterogeneity, ranging from reddish Alfisols (Hapludalfs in the USDA Soil Taxonomy, 1999; Chromic Luvisols in the FAO-ISRIC WRB, 1998)  in the Upper Pleistocene plain to fine-textured Inceptisols with vertic or gleyic  characters (Typic, Vertic and Aquic/Oxyaquic Eutrudepts in S.T.; Cambisols, Calcisols and Gleysols in the WRB) in the late Wurmian-Holocene plain, and to fine, gleyed Entisols (Fluvents, Aquents in S.T.; Fluvisols, Gleysols in the WRB) and coarse-textured Entisols (Psamments in S.T.; Arenosols in WRB) in recent sandy deposits which border the lagoon. In lowland and wetland areas, where organic matter accumulates, Mollisols (Phaeozems in WRB) and Histosols occur.
In the gently ondulating landscape of Tertiary age (Soil Region 16.5, Cambisols-Leptosols Region), soils are mostly Inceptisols (Eutrudepts or Dystrudepts in S.T.; Eutric or Dystric Cambisols with some andic characters in the WRB). Entisols are mostly Typic and Lithic Udorthents in S.T., and Eutric or Rendzic Leptosols in the WRB.
In mountain areas (Soil Region 34.3, Leptosols Region with Cambisols), Inceptisols and Mollisols  with weakly differentiated profile (Udepts, Udolls, Rendolls in S.T.; Calcari-Mollic Cambisols or Phaeozems in the WRB) are the prevailing soils, with subordinate podzolic soils (Haplorthods in S.T., Haplic Podzols in the WRB) and eroded, shallow Entisols (Udorthents in S.T., Rendzic or Dystric Leptosols or Regosols in the WRB).

2.2 Laboratory methods
900 soil samples (both topsoil and subsoil) from more than 300 representative soil profiles were selected for standard soil characterization and trace elements analysis. The sampling sites (446 from agricultural areas, 454 from rangeland and forest areas, 10 from urban areas and the lagoon border) were selected following the soil typological approach (ARPAV, 205) within the four pedolandscapes previously described, comprehensive of parent material, relief and land use.
Samples were air-dried and passed through a 2 mm sieve in order to separate coarse fragments from the fine earth. Standard laboratory methods established by the Italian Ministry of Agriculture (MIRAAF, 1994) were applied on the fraction <2 mm, and included: particle-size distribution (pipette method following organic matter removal with H2O2 and dispersion with sodium metaphosphate); pH (1:2.5 soil-water suspension); total carbonates (gas-volumetric method); readily oxidizable organic carbon (Walkley-Black method); cation exchange capacity (titration with EDTA after extraction with triethanolamine and BaCl2 buffered at pH 8.2). Exchangeable bases were determined by AA spectrometry, after BaCl2 and triethanolamine extraction. 
A fraction of the fine earth (<2mm) was finely ground in a agate mortar to obtain a homogeneous powder (<100µm). Heavy metal concentrations in soils were quantified, after digestion in acidic mixture for total (“aqua regia”: ISO 11466) and DTPA-extractable (ISO 14870) fractions. Instrumental determination of metals (As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Zn) was performed by atomic absorption spectroscopy on the fine fraction (<100µm) of the soils previously selected.

2.3 Statistical analyses
 
Univariate and multivariate statistical analyses were applied to the data set. The recorded data were statistically processed with the software STATISTICS for Windows, version 2002.
Frequency distribution and Pearson correlation matrices were calculated in order to evidence simple and multiple correlations between variable pairs. Principal Component Analysis (PCA)  was applied for reducing the number of variables in the data set to a few components or factors, and therefore identifying the relationships between the variables, to enhance data variability interpretation. Varimax rotation of the factors was used to maximize the variance explained by each principal component (Hair et al., 1998). Hierarchical cluster analysis was also used to highlight similarities between sampling sites, and to verify the consistent associations between sampling sites and groups of elements (pedogeochemical fingerprints).

3.	Results and Discussion.

3.1. Agriculture Soils

The territory investigated covers approx 160,000 ha and extends from the lagoon borderline up to 50 kilometers over about 1/4 of the whole agriculture areas in North Eastern Italy, mostly in the alluvial plain.
The soils examined (200 sites, totaling 446 soil samples) were grouped in 5 orders and 11 subgroups of the Soil Taxonomy (USDA, 1999); Inceptisols (77%) are the most represented, followed by Entisols (15%) and Alfisols (5%); Mollisols (2%) and Vertisols (1%) complete the whole set of soils in the agricultural area. (Fig. 2).

The mean levels, variance and ranges of soil properties (pH, organic matter, total carbonates, CEC and particle size distribution) are reported in Table 3.

Table 3 – Descriptive statistics for agricultural soil properties (446 soil samples, 223 topsoil, 226 subsoil).

	pH	Organic Carbon %	Total Carbonates %	CEC cmol(+)/kg	Clay %	Silt %	Sand %	
Mean	8.11	2.15	17,25	19.54	27.51	45.14	27.35	
Median	8.23	1.06	10	17.71	25.54	44.26	24.88	
Standard deviation	0.45	3.82	17.56	9.28	12.74	11.67	18.99	
minimum	4.83	0.2	0	2.30	1.92	1.17	0.4	
maximum	8.9	4.3	82	64.71	64.30	70.05	96.35	

A wide range of values was found for all the determined parameters. The  pH value ranges between 4.8 and 8.9, accordingly to the nature of parent material and pedogenic processes. Mean Organic Carbon level is 2.1%, with the maximum 4.3% in surface horizons of Mollisols; total Carbonates also have a wide range (0-82%), with very high variance, in relation to the parent material characteristics and to leaching processes within the soil; CEC ranges from 2.30 to 65 cmol(+)/kg, depending on the particle size composition. The soils have also a great variability in grain size distribution (2 - 64 % clay, 1-70% silt, 0.4-96% sand), in relation to the parent material composition and the site morphology.

The mean values, variance and ranges  of total heavy metal concentrations (mg/kg d.m.) in the soils examined are summarized in Table 4.

Table 4 - Descriptive statistics for total heavy metal concentrations (mg/kg d.m.)
	Cd	Co	Cr	Cu	Mn	Ni	Pb	Zn	As	Hg	
Mean	0.52	9.95	32.55	52.97	581.98	32.55	24.14	90.27	13.72	0.22	
Median	0.51	9.77	28.55	36.2	529	22.5	22.6	88.35	10.75	0.15	
Standard deviation	0.248	4.12	19.00	49.35	257.24	40.64	15.64	32.55	11.05	0.23	
minimum	0	1.57	4.67	3.05	147	3.1	0.72	12.6	0	0	
maximum	1.65	31.5	149	362	1573	413	203	201	65.1	1.24	

The soils present generally high levels of heavy metals, with mean values of 53 mg/kg total Cu (range 3 - 362), 90 mg/kg total Zn (range 13 -201), 32 mg/kg total Ni (range 3 - 413), 32 mg/kg total Cr (range 5 - 149); Pb (mean 24 mg/kg), Co (mean 10mg/kg) and Cd (mean 0.5 mg/kg) present higher concentrations in organic horizons than in mineral horizons (data not shown). Of the volatiles, mean total As is 14 mg/kg (range 0 - 65), while Hg (mean 0.2 mg/kg) presents low and uniform concentration along the soil profile. The highest metal concentrations, far above the regulatory threshold for contamination (see Table 1), were recorded especially in surface horizons (data not shown), as it was reported also in a recent work on soils of a portion of the alluvial plain (Ungaro et al., 2008). 
Arsenic is an environmental issue in the Veneto region, since its concentration is currently (in 30% of the samples examined) above the regulatory threshold for contamination (20 mg/kg). The origin of As high concentration in soils is related to two main factors: rock composition and human activities. Volcanic and mine areas contribute to naturally high As concentrations in soils, whilst combustion of fossil fuels, agrochemical application, smelting etc. are the main anthropic As sources (Ungaro et al., 2008). The spatial distribution of As concentration in topsoil in the Venice watershed is reported in Fig. 3. A clear  anthropogenic input is localized in the central area, not far from the Venice industrial area, while some hotspots of lithogenic origin are localized in the volcanic area of the  Euganean hills (southwestern zone).
Nickel also presents, in the same volcanic area, a few hotspots ( 3.4% frequency within the whole data set) with concentration levels higher than 75 mg/kg, although in the whole region most soils have low Ni concentrations (<25 mg/kg in 65% of the examined samples).
Zinc and copper are known as critical micronutrients for plants, and are largely utilized in agriculture to combat vineyard diseases. Their concentration in surface soil horizons, therefore, is frequently above the regulatory threshold for contamination. In the whole set of samples, Zn contents (Fig. 4) account for 72% in the > 75 mg/kg concentration class, and for 5% in the >150 mg/kg class; Cu contents account for 30% in the >50 mg/kg, and for 15 % in the  >100 mg/kg concentration class (Giandon et al., 2000). It is very likely that zinc and copper pollution of surface horizons could be a consequence of agrochemical compounds containing these metals and even As (Deluisa et al., 1996). 
Some Pb hotspots (3% of the whole set of samples with concentration >50 mg/kg, with a maximum value up to 203 mg/kg; Fig. 5) and Cd accumulation (17% of the whole set of samples with concentration >1 mg/kg) were recorded in areas close to the Venice industrial zone, and in the northern part, close to the forested area, suggesting an anthropogenic input from both industrial emissions and atmospheric pre-alpine deposition.

Metal speciation is an useful tool to identify different chemical bonding of the metal with the soil inorganic and organic colloids (Goupta et al., 1994). The DTPA- extractable metal concentrations were determined in the same set of samples as above, in order to assess possible soil contamination and to distinguish lithogenic and anthropogenic metal inputs. The results are summarized in Table 5.  

Table 5 – Descriptive statistics for DTPA-extractable heavy metal concentration (mg/kg d. m.) in the soils examined.

	Fe	Mn	Zn	Cu	Ni	Pb	Cd	Cr	
Mean	28.53	15.69	2.51	12.09	0.43	3.66	0.077	0.058	
Median	18.2	12.10	1.51	6.31	0.315	3.20	0.080	0	
Standard deviation	65.99	13.24	3.07	16.70	0.61	2.84	0.057	0.080	
range	1307.31	112.39	24	112	7.04	28.6	0.82	0.31	
minimum	1.69	0.61	0	0	0	0	0	0	
maximum	1309	113	24	112	7.04	28.6	0.82	0.31	

The DTPA-extractable metal concentration presents a significant reduction with respect to the total amount, as expected. Mean extractable Cu was l2mg/kg, Zn 2.5mg/kg (very low concentration, possible deficiency in plants), Pb 3.7 mg/kg, Cd 0.08 mg/kg, Ni 0.4 mg/kg, Cr 0.06 mg/kg. However, important concentrations were recorded especially for  Cu (112 mg/kg), Pb (29 mg/kg) and Cd (0.8 mg/kg). This suggests that these elements could be, almost in part, linked to organic colloids of anthropic origin (Cu from agrochemicals, Pb and Cd from atmospheric and industrial emissions). Instead, Ni and Cr concentrations could be in relation to the lithological matrix. Similarly, the low iron and manganese extractable fraction (mean 28 mg/kg, and 16 mg/kg, respectively) could be related to the limited mobility of these two elements, as determined by the oxidation-reduction conditions. 

The whole data set (soil characteristics, total and DTPA-extractable metal concentrations) was statistically processed in order to find relationships between the variables, which could better explain environmental processes and possible soil contamination. The correlation matrix is shown in Table 6. 

Table 6 - Correlation coefficients matrix. Values >0.6 are in bold.

	pH	O.C.	CaCO3	clay	silt	sand	CEC	Fe_av	Mn_tot	Mn_av	Zn_tot	Zn_av	Cu_tot	Cu_av	Ni_tot	Ni_av	Pb_tot	Pb_av	Cd_tot	Cd_av	Cr_tot	Cr_av	Co_tot	
pH	1																							
O.C.	-0,1350	1																						
CaCO3	0,4434	-0,0606	1																					
clay	-0,0183	-0,0099	-0,1741	1																				
silt	0,2444	0,0294	0,3179	0,3935	1																			
sand	-0,1520	0,0043	-0,0439	-0,7271	-0,8479	1																		
CEC	-0,1155	0,1608	-0,2962	0,7358	0,2460	-0,5168	1																	
Fe av	-0,2048	0,0660	-0,1117	0,0403	-0,0323	-0,0060	0,0608	1																
Mn tot	-0,1738	-0,0584	-0,4292	0,2600	0,0316	-0,1890	0,2533	0,0572	1															
Mn av	-0,4348	-0,1092	-0,3404	0,0539	-0,1820	0,0931	0,0358	0,0791	0,4842	1														
Zn tot	-0,1424	0,2930	-0,5168	0,2525	0,0198	-0,1889	0,3173	0,0638	0,3074	-0,0054	1													
Zn av	-0,0891	0,0329	0,1474	-0,1947	-0,1069	0,1673	-0,1011	0,0500	-0,0191	0,1037	0,1878	1												
Cu tot	0,0092	0,1104	0,0124	0,0347	0,0554	-0,0852	0,1056	-0,0224	0,1577	-0,0284	0,1995	0,4878	1											
Cu av	-0,0032	0,0709	0,1037	-0,1101	0,0096	0,0159	-0,0478	-0,0155	0,0548	-0,0134	0,1024	0,5951	0,9269	1										
Ni tot	-0,0658	-0,0217	-0,1168	0,3542	0,0985	-0,2429	0,4867	0,0041	0,3075	-0,0707	0,1593	-0,1182	0,0592	-0,0755	1									
Ni av	-0,2669	0,1377	-0,0696	0,2359	0,0342	-0,1358	0,4604	0,1999	-0,1277	0,0652	-0,0318	0,1331	-0,0087	-0,0413	0,1979	1								
Pb tot	-0,2260	0,0654	-0,4121	0,0758	-0,1280	0,0296	0,0765	0,0955	0,2956	0,2648	0,4570	0,1344	0,0287	0,0178	-0,1563	-0,0333	1							
Pb av	-0,0988	0,1983	-0,1705	0,0179	-0,079803	0,0354	0,0397	0,0771	0,0070	0,0544	0,3895	0,2524	0,2020	0,1873	-0,1660	-0,0058	0,5877	1						
Cd tot	-0,1408	0,3052	-0,5184	0,0542	-0,0912	-0,0209	0,1188	0,0662	0,3498	0,2009	0,6010	-0,0322	0,0821	0,0117	-0,1598	-0,1677	0,4789	0,3452	1					
Cd av	-0,1919	0,3083	-0,2083	0,0045	-0,1199	0,0387	0,0878	0,1127	0,1827	0,2969	0,2379	0,3189	0,3649	0,3479	-0,1212	0,1713	0,2542	0,3104	0,3641	1				
Cr tot	-0,0790	0,0221	-0,3094	0,6486	0,1575	-0,4309	0,6923	0,0034	0,3563	-0,0101	0,2920	-0,1676	0,0721	-0,1062	0,8027	0,2735	-0,0639	-0,1148	-0,0499	-0,074173	1			
Cr av	0,0144	-0,1224	0,3251	0,2935	0,3499	-0,3740	0,2673	0,0130	0,0037	-0,1702	-0,2275	0,3125	0,4017	0,3711	0,3807	0,3440	-0,4186	-0,2029	-0,5078	-0,037687	0,362733	1		
Co tot	-0,1371	0,1338	-0,5450	0,5429	0,1159	-0,3825	0,5937	0,0404	0,6567	0,1650	0,5344	-0,1673	0,1647	-0,0335	0,4715	0,1235	0,2392	0,0464	0,4310	0,127998	0,699727	0,042608	1	

Statistically significant correlations (p<0.05) are observed between soil properties and metal concentration. Clay content exhibits positive correlation with Cr (r=0.648), and Co (r=0.542), sand content  relates negatively to Cr (r=-0.43) and Co (r= -0.38), suggesting these two metals to be mostly of lithogenic origin; CEC relates to Cr (r=0.69) and Co (r=0.53)  again, confirming their lithogenic origin; total carbonates relate to Zn (r=-0.52) and Cd (r=-0.52), suggesting antagonism between Ca and the two microelements. 
A statistically (p<0.05)  positive correlation between some element couples (e.g. Ni/Cr 0.802; Zn/Cd 0.601; Mn/Co 0.656; Cr/Co 0.699; Zn/Co 0.534) and some soil parameters (e.g. Clay/CEC 0.735) was found.
Negative correlations are exhibited with sand and clay (r= -0.727), sand and CEC (r=- 0.516), sand and silt (r=- 0.847), as expected. Bioavailable element fraction too exhibits positive correlations with total concentration (Cu tot/Cu av 0.927; Pb tot/Pb av 0.587; Cu av/Zn av 0.595). The correlations exhibited with pH and O.M. are insignificant. These results suggest the bioavailable fraction to be most likely related to the anthropic origin of the metals examined.

The principal component analysis (PCA) was applied to the whole data set. The components were rotated using a varimax rotation (Hair et al., 1998), which maximizes the variance of the squared normalized factor loadings across variables for each factor. The multivariate statistics allowed separation of the 23 variables considered into seven principal components, which account globally for 73.88 % of the variance. Only the first sixth principal components with eigenvalues greater than one were selected for factor analysis.
Due to the large heterogeneity of the data set, and the high number of variables (23), the loading factors show (Table7) values generally lower than 0.5. Nevertheless, significant information could be achieved from the PCA.
The largest loadings for the first component, which accounts for 20 % of the  observed variance, were recorded for total Co, Cr, Cu, Mn and Zn, an for CEC, clay and CaCO3. The second component, which accounts for 17.7 of the observed variance, showed the largest loadings for Cd, Pb, sand and negative loadings for silt. The third component was mostly represented by bioavailable metal concentrations, with negative loadings for Cd, Cr, Zn, Cu and total Cu. The fourth component included pH, and available Ni with negative loading. The fifth component had negative loadings for Organic Carbon and available Pb. The sixth component accounted for only 5.5 of the variance, and exhibited negative loadings for available Mn and Fe, and positive loading for total Ni.
The separation of most of the total and available heavy metal concentrations in different groups of components (PC1 and PC3, respectively) indicates that the prevailing origins of the total elements should be different from those of the available ones, as previously discussed, and found also by Ungaro et al. (2008) in soils of the Brenta river alluvial plain..

Table 7 – Factor loading matrix from Principal Component Analysis of 23 soil variables. Values with loading factors >0.25 are in bold (tot=total; av=available)

Variables	PC1	PC2	PC3	PC4	PC5	PC6	
Co tot	 0.389	0.003	0.062	0.029	0.194	0.086	
CEC	 0.350	-0.152	0.004	-0.048	-0.184	0.072	
Cr tot	 0.339	-0.196	0.065	-0.161	0.107	0.220	
Clay	 0.324	-0.210	0.044	-0.129	-0.129	-0156	
Zn tot	 0.278	0.179	-0.059	0.238	-0.017	-0.248	
Mn tot	 0.273	0.088	0.024	-0.040	0.268	-0.268	
CaCO3	-0.266	-0.259	-0.160	0.118	-0.104	-0.082	
							
Cd tot	 0.189	 0.295	0.044	0.024	0.024	0.036	
Pb tot	 0.156	 0.282	0.006	0.115	-0.015	-0.188	
Sand	-0.231	 0.267	0.061	0.027	0.027	-0.238	
Silt	 0.089	-0.286	-0.086	0.059	0.059	-0.272	
							
Cd av	 0.115	0.219	-0.252	-0.148	-0.148	-0.109	
Cr av	 0.058	-0.307	-0.311	0.032	0.032	-0.053	
Zn av	-0.028	0.098	-0.442	-0.046	-0.046	-0.031	
Cu tot	 0.090	0.030	-0.506	0.199	0.085	0.085	
Cu av	 0.006	0.054	-0.532	0.174	0.028	0.028	
							
pH	-0.128	-0.172	-0.020	 0.358	0.177	0.159	
Ni av	 0.128	-0.089	-0.073	-0.323	-0.459	0.017	
							
O. C.	 0.088	0.093	-0.088	0.137	-0.347	0.351	
Pb av	 0.087	0.222	-0.159	0.227	-0.258	-0.004	
							
Mn av	 0.112	0.187	 0.046	-0.248	0.089	-0.558	
Fe av	0.058	0.057	-0.014	-0.133	-0.275	-0.338	
Ni tot	 0.236	-0.202	0.039	-0.223	 0.181	 0.280	
							
eigenvalue	 5.0	4.4	2.9	2.0	1.6	1.4	
Variance%	 20.0	17.7	11.6	8.4	6.4	5.5	
Cum. Var.%	 20.0	37.7	49.3	57.4	63.8	69.3	

The distribution of the scores of the loading factors in the scatterplot of the principal components 1 and 3 shows (Fig. 6) that total heavy metals (with the exception of Cu), CEC and clay present positive scores for both PC1 and PC3, while available heavy metals present very high negative scores for the PC3. Soil total carbonates present negative scores for both PC1 and PC3.
Soil horizon differentiation in the PC1-PC3 scatterplot (Fig. 7) shows a concentration of values related to the A horizon around the zero, with a dispersion towards negative PC3 scores (anthropic origin). On the contrary, samples representing the B horizons have positive scores for PC3, and samples from the C horizons have PC1 scores approximately = zero.
The spatial distribution of the soil samples in the PC2/PC3 scatterplot according to their specific properties (corresponding to the taxonomic level of subgroup: vertic, aquic, oxyaquic, fluventic, alfic, typic) allows identification of individual domains where every soil property (i. e: pedogenic character) is prominent (Fig. 8). Soils having vertic properties (i. e. the geological factor) are dispersed from the zero towards negative PC3 values, while soils of the subgroups aquic and oxyaquic (i. e. hydrological factor) are located in the vicinity of the zero, the subgroup fluventic (i. e. organic matter factor) presents positive scores for PC3, and the subgroups alfic and typic (i. e. leaching factor) are scattered, being independent from both PC2 and PC3. These results suggest that every pedogenic factor prevails over the others in determining element mobility and therefore in controlling the soil evolution (Bini and Zilocchi, 2001).
Interpreting the PC analysis in terms of processes occurring in the soil, and fate of trace elements in the soil environment, the PC1 accounts for elements of lithogenic origin, as indicated by their association with CEC and clay. On the contrary, PC2 is expression of the anthropogenic origin for total Cd and Pb, which are positively associated with sand, and negatively with silt: This suggests that waste disposal and atmospheric deposition are the main sources of these metals in the area, as suggested also by Scazzola et al. (2004) . Moreover, because of its low  mobility, Pb is still enriched in soils polluted by traffic emissions (Norra et al., 2006).
The PC3 accounts for bioavailable microelements of likely anthropogenic origin. Agrochemicals from agricultural areas and metallurgy from local plants are the main trace element sources. Most of the sampled sites are located at distance less than 30 km from the industrial area of Porto Marghera, and therefore contamination may explain the enrichment in available metals, which are likely contributed by surface reactions, adsorption onto other mineral phases (Norra, 2006) or by biogeochemical cycles (Sterckeman et al., 2004). The same is true of Factor 5, where a strong association of available Pb with organic carbon is observed, in accordance with the results obtained by Sterckeman et al. (2004) in soils developed on recent marine deposits of Northern France.
Factor 4, which relates pH to available Ni, does not give more information with respect to the correlation coefficients (Table 6), confirming the pH to be ineffective with respect to element mobility in the present soil environment.
Oxidation-reduction conditions seem to have a selective effect on the association of available Mn and Fe in Factor 6.

 

3.2. Rangeland and Forest Soils.
The investigated rangeland and forested areas extend over approximately 40,000 ha (20% of the whole area), mostly in mountain areas. Mesophile mixed woods (oak, elm, holmbean, ash, maple), with subordinate beech and spruce stands, are the most important forest components, while limestone is the dominant parent material. 
The soils examined (120 sites were established, totaling 454 samples (188 from topsoil and 266 from subsoil, of which 142 were from the C horizon) were grouped in seven Great Groups of the Soil Taxonomy (1999), as a function of  parent material and pedogenetic features. Their partitioning is shown in Fig. 9. Inceptisols (50%) and Mollisols (42%) are the dominant soil orders. Entisols (4%), Alfisols (2%) and Spodosols (2%) complete the soil geography of the area.
The mean levels, variance and ranges of pH, organic matter, total carbonates, CEC, particle size distribution are reported in Table 8.

Table 8 – Descriptive statistics for rangeland and forest soil properties	
	pH	O.C. %	Total Carbonates
 %	CEC cmol(+)/kg	Clay %	Silt %	Sand %	
Number of samples	454	188	119	312	454	454	454	
Mean	5.0	25.5	32	22.45	14.5	21.20	20.88	
Variance	19	31	14	116	129	55	87	
Min	3.3	10.1	0	5.60	1.6	1.35	0.60	
Max	7.4	44.6	64	52.34	56.2	47.92	91.80	

Table 9 – Descriptive statistics for total heavy metal concentrations (mg/kg d.m.) in rangeland and forest soils examined.
	Al	Fe	Mn	Zn	Cu	Ni	Pb	Cd	Cr	
Mean	13793	17020	1044	166	23	22	120	2.4	27	
Variance	57	48	81	42	38	72	61	61	64	
Min	2320	3490	94	73	12	3	33	0.7	4	
Max	36500	36680	4715	588	77	70	549	6.7	87	

Most soil horizons (61%) have acidic reaction, with mean pH = 5.0 (range 7.4 - 3.3), though many are developed from calcareous rocks; this suggests that decarbonation and leaching occurred in the investigated area as a consequence of high annual precipitation (map =1200 mm).
The organic matter content is generally high (mean 255 g/kg, range 446-101) at surface, and decreases with depth, the richest horizons being those from calcareous parent material (mollic epipedon).
Total carbonates range from 0 to 64% (in very calcareous soils), but CaCO3 levels higher than 20% occur only in 33% of the samples. The CEC presents a mean value of 22 cmol(+)/kg  and a very high variance (range 5-52 cmol(+)/kg), with 71% of the examined samples having more than 18 cmol(+)/kg CEC. The particle size distribution points to large differences in the percentage of single components, with high variance for clay and also for sand, depending on the parent material characteristics, the site morphology and the soil evolution.

The results obtained with the total content of the elements investigated (Table 9) show that heavy metals present contents generally within the reference values reported in Table 1, with the exception of  Zn (mean 166mg/kg), and Pb (mean 120 mg/kg). However, total Cr (mean 27 mg/kg, range 4-87 mg/kg) exceeds the threshold in 12% of samples, Ni (mean 22 mg/kg, range 3-70 mg/kg) in 8%, while Mn presents some high contents (up to 4700 mg/kg) at some sites.
The heavy metal concentration in the “C” horizon may be considered the pedogeochemical background in the pedosphere (Sterckeman et al., 2004). The mean metal concentration in the C horizon of the profiles investigated (Zn 77mg/kg; Cu 12 mg/kg; Cr 27 mg/kg; Ni 15 mg/kg; Pb 40 mg/kg; Cd 0.5 mg/kg; Mn 400mg/kg; Fe 3490 mg/kg) is within the “normal” range for soils of western Europe (Angelone and Bini, 1992). Surface horizons, however, present elemental concentrations higher than C horizons (Zn up to 132 mg/kg; Cu 21 mg/kg; Cr 55 mg/kg; Ni 37 mg/kg; Pb 69 mg/kg; Cd 1.4 mg/kg), while mean levels of trace elements in the B horizon are lower than those in the A and C horizons. Moreover, anthropogenic Pb (mean 120 mg/kg, range 33-549 mg/kg) and Cd (mean 2.4 mg/kg, range 0.7-6.7 mg/kg) are strongly accumulated (50% and 70% of the examined samples, respectively) especially at surface, due to their known affinity with organic matter, as reported also by Sterckeman et al. (2004). Such accumulation is very likely related to atmospheric inputs from acidic precipitation which has affected Northern Italy for many years (Bini and Michelutti, 1997; Bini et al, 2003). A confirmation of this statement is that heavy metal contribution by acid rains to the forest soil in the Cansiglio Integral Biological Reserve (80km North-East from Venice) was recorded in two experimental plots under beech and spruce, during 1997 (Bini and Bresolin, 1998).
As regards Pb, however, it is important to point out that highest concentrations in the soils investigated were recorded in a mine area at a distance of approximately 120km from Venice. Similarly, it was demonstrated (Dubois et al., 1998) that Cd in soils may derive partly from the calcareous parent material. Hence, in both cases the geological matrix effect must be summed to that of anthropogenic contribution. 

The univariate statistical analysis of the whole data set accounted for significant (p<0.05) positive correlation of some element couples (Table 10). Chromium correlates well with Ni (r= 0.896) and with Fe (r=520), and moderately with Zn and Cd; Zn is well correlated with Mn (r=0.694) and Pb( r= 0.697), and moderately correlated with Cd and Cr; Pb and Zn are well correlated with Mn (r=0.618; r=0.694, respectively). Moreover, Cr and Ni are significantly correlated with particle size (negative correlation with sand, and positive correlation with silt and clay). Silt and clay are negatively correlated with sand, as expected.
The organic carbon and the pH do not show significant correlations, as with the agricultural soils.

Table 10 – Correlation coefficient matrix (values at p<0.05 are in bold)
 	O. C.	Fe	Mn	Cd 	Cr 	Cu	Ni 	Pb 	Zn 	pH	Sand 	Silt 	Clay	
O. C.	1													
Fe	-0,11	1												
Mn	-0,17	0,37	1											
Cd 	0,197	0	0,265	1										
Cr 	-0,10	0,520	0,336	0,493	1									
Cu	0,001	0,13	0,112	0,035	0,095	1								
Ni 	-0,18	0,460	0,403	0,36	0,896	0,149	1							
Pb 	-0,04	0,01	0,618	0,139	-0,015	0,014	-0,019	1						
Zn 	0,002	0,35	0,694	0,414	0,407	0,157	0,3805	0,697	1					
pH	-0,25	-0,46	-0,08	0,35	0,17	-0,028	0,1842	-0,071	-0,08	1				
Sand 	-0,26	-0,2	-0,22	-0,407	-0,636	0,03	-0,526	-0,058	-0,24	-0,14	1			
Silt 	0,286	0,16	0,234	0,46	0,539	-0,018	0,496	0,0221	0,19	0,232	-0,630	1		
Clay	0,105	0,27	0,302	0,242	0,647	0,05	0,646	0,1098	0,29	0,004	-0,576	0,309	1	

The multivariate statistics allowed subdivision  of the variables (totally 18 variables) into five principal components (Table 11), which cover globally more than 90% of the cumulative variance. Only the first three principal components have eigenvalues >1, and will be discussed here. PC1 accounts for 50% variance, PC2 19%, PC3 12%.
PC1 accounts for positive scores of trace elements (Cr, Ni, Zn, Cd, Mn), silt and clay, and a strong negative score for sand; therefore, it may be considered an expression of mineral weathering and  mobilization of elements of lithogenic origin. PC2 accounts for negative scores for carbonates and pH, and positive scores for Fe, suggesting to be expression of specific pedogenetic processes (i. e. carbonation, brunification) and redox conditions within the soil. Therefore, PC2 distinguishes well calcareous soils from acid ones. PC3 accounts for positive scores of the soil organic components  (organic carbon and nitrogen), and therefore is an expression of humification processes, and Pb, confirming the strong affinity of this metal with organic matter, as previously stated. PC4 accounts for highly negative scores for exchange acidity and amorphous iron. This component, therefore, illustrates the highest weathering processes in acidic environment, like leaching and podzolisation.

Table 11 - Principal Component Analysis of 18 soil variables (p<0.05). Values with loading factors >0.6 are in bold

	PC1	PC2	PC3	PC4	PC5	
Sand	-0.9439	0.0552	-0.2328	0.0789	-0.1465	
Cr	0.9419	0.2133	0.1533	0.1504	0.1186	
Ni	0.9227	0.1810	-0.1397	0.1603	0.1944	
Clay	0.9029	0.2028	0.2004	-0.0768	-0.0858	
Silt	0.8702	-0.1171	0.4401	0.0760	0.0769	
Zn	0.7200	0.5130	0.3608	0.1197	0.1101	
Mn	0.6987	0.6194	-0.1084	0.1619	0.0584	
Cd	0.6305	-0.3112	0.4431	0.2431	0.1032	
						
CaCO3	-0.1218	-0.9337	-0.1138	0.1515	-0.2079	
Fe	0.3620	0.8910	0.0497	-0.1003	0.1550	
pH	0.1743	-0.8620	-0.1677	0.4018	0.0804	
						
O.C.	0.1444	0.1473	0.9107	-0.2955	0.1053	
N	0.1072	-0.0487	0.8911	0.0296	0.1200	
Pb	0.5067	0.3420	0.6733	0.0049	0.0813	
						
Acidity	-0.2175	0.2202	-0.0296	-0.8696	-0.0561	
Fe ox	0.0618	0.4985	0.3224	-0.6990	0.1004	
						
CEC	0.1806	0.3371	0.5364	0.0586	0.6629	
Cu	0.5575	0.3618	-0.0163	-0.0311	0.6046	
						
eigenvalue	9,9	3.8	2.4	0.9	0.8	
Variance%	49.9	19.3	12.2	4.9	4.1	
Cum. Var.%	49.9	69.2	81.4	86.3	90.4	

Interpreting the PCA in terms of pedogenesis, the distribution of variables in the PC1/PC2 scatterplot (Fig. 10) allows distinction of strongly weathered horizons from silicate rocks (podzolic soils, group 5, and acidic soils, group 4) with positive loadings for PC1 and PC2,  from slightly altered horizons from calcareous parent material (Mollisols, group 1, and Inceptisols, group 2), brunified and leached subsurface horizons (groups 2, 3) and from organic-matter rich horizons of less developed soils (A horizons of Mollisols, Entisols and Inceptisols, Groups 1, 2, 3).
In the PC1/PC3 scatterplot (Fig. 11),  the component 3 identifies soil samples involved in humification processes: the A horizons, indeed, account for high PC3 loadings for soils of groups 1, 2, 3, and slight loadings for soils of groups 4 and 5. The variable “sand” in the component 1 shows a strong loading in the C horizons, which are obviously influenced by the parent material composition. Conversely it shows little loading with horizons having marked pedogenic evolution, as in soil groups 4 and 5.
In the PC2/PC3 scatterplot (Fig. 12), the component 2 separates thoroughly subalkaline soils (groups 1-2) from acid soils (groups 4 – 5). The component 3, instead, allows separation of 
Acidic soils (groups 4, 5) and leached soils (group 3) from calcareous ones (groups 1, 2) and, within the latter, the surface horizons originated by humification processes, from the subsurface ones, which are contributed by parent material.
The cluster analysis carried out on the same set of samples (Fig. 13) gives adjunctive  information on the similarity among soil properties and soil horizons. Soil properties are clearly grouped according to their affinity (e. g. organic carbon with CEC and Pb, pH with CaCO3, exchange acidity with extractable Fe, total Fe, Ni, Cr, with Mn, Cu with Zn), as expected. Some pedogeochemical fingerprints, therefore, are highlighted with clustering. In terms of pedogenic horizons genesis, subalkaline surface horizons (A horizons, groups 1, 2, 3) are clearly separated from the acid ones (A4-A5 horizons). The parent material too is clearly distinguished in calcareous (C1-C2-C3) and acidic (C4-C5) components. Moreover, the pedogenetic continuity within the different soil profiles is evident in leached and podzolic soils (A3-B3, A5-B5 horizons),as well as in subsoil horizons of acidic soils (B4-C4 horizons) and of calcareous ones (B1-C1 horizons). The only B2 horizons do not show any similarity. This may be explained by the intermediate character  of these horizons, originated  by slight weathering during the brunification processes. However, at higher level of similarity, they are clearly related to subalkaline parent materials of soil groups 1, 2 and 3.

3.3. Inland coastal areas and lagoon sediments  
The inland coastal areas and the lagoon of Venice constitute a complex system which has been, and is currently, affected by human activities (industry, agriculture, settlements, tourism) that impact severely the ecosystem. Discharge from the agricultural drainage basin affect particularly the area North of the city of Venice, where the Dese river is one of the main inputs of agrochemical contaminants (Argese and Bettiol, 2001). The central and southern areas, instead, receive important pollutant inputs from the industrial zone of Porto Marghera, where a number of chemical and petrochemical plants operate since the ‘50s (Bernardello et al., 2006). Additional sources of pollution are domestic sewage and waste disposal from the urban area. These inputs have progressively deteriorated the land quality, and are chronologically related to the development of the industrial and urban areas (Pavoni et al, 1987; Bernardello et al., 2006). As a consequence of the increasing land contamination, significant amounts of contaminants are accumulated in soils of the borderline and in the lagoon sediments, which may constitute a potential source of secondary pollution (Turetta et al., 2005).
Results of surveys carried out in recent years on the mainland (Scazzola et al., 2003; 2004) and on the lagoon sediments (Bernardello et al, 2006; Zonta et al., 2007) show that heavy metal concentration increased from the beginning of the industrial activities in the area until the ‘90s, when Porto Marghera declined. From that period, following new regulatory guidelines, a survey of the whole watershed and systematic monitoring of  water, air and soil pollution have been conducted. Increasing heavy metal concentration was detected along a transect from the mainland (undisturbed soils of agricultural land, more than 40 km far from the city of Venice) to urban soils close (less than 5 km) to Porto Marghera industrial area, and to the inner border of the lagoon (Scazzola et al., 2004). A set of 10 soil profiles was selected from areas with different land use, in order to assess previous metal concentrations and possible contamination levels.
Most of the metals have concentrations above background values (Table12), with Cd, Cr, Hg, Zn in lagoon sediments showing the highest values. The highest metal concentrations were found in  an area between Porto Marghera and the city of Venice, where both industrial and urban sewage are discharged. The concentration gradient for most metals (Cd, Cr, Cu, Hg, Mn, Ni, Zn) decreases from the inner margin of the lagoon to both the outer border and the mainland, suggesting that the inputs from the industrial area represent the main factor influencing the metal spatial variability. The spatial gradient of concentrations, therefore, is an index of overall pollution. However, sediment re-suspension and dispersion of fine particles by tidal currents may contribute to the recorded distribution pattern. 

Most of the trace elements in samples examined  were positively correlated with fine particles (<53 μm), supporting the importance of particle size in influencing metal accumulation, as it was found in previous works by Sterckeman et al. (2004) and Bernardello et al. (2006). Adsorption, surface diffusion, formation of precipitates onto other mineral phases like Fe oxides could be the form the heavy metals accumulate.
Two groups of metals (Fe, Mn, Cr, Ni, and Cd, Cu, Pb, Zn, respectively) have been found by Zonta et al. (2007) showing high correlation coefficients among them (Fe-Mn =0.94; Fe-Ni =0.92; Fe-Cr= 0.93; Pb-Cu=0.97; Cd-Zn=0.80; Cu-Zn=0.89) and with clay (clay-Ni= 0.87; clay-Cr=0.79; clay-Cu=0.83; clay-Pb=0.87). Similar results were obtained by Turetta et al. (2005), who performed a PCA on samples from the lagoon sediments and found a clear separation between two groups of metals: high positive scores for  As, Mn, (factor 1) and Zn and Cd (factor 2), low score for Cu. 
The impact of anthropogenic activities on the composition of surface soils can be demonstrated by metal abundances  in sediments of the inner lagoon margin, as well as in urban soils (Table 12), as demonstrated also by Norra et al. (2006) and Fitzpatrick et al. (2007) in urban soils from Germany and U.S.A. In a PCA carried out on soil samples from different sites, Norra et al. (2006) found that the spatial distribution of metal concentration increases from forested areas to agricultural soils and from low density settlements to high density settlements and industrial areas. Similar results have been recorded in samples from the surroundings of the Venice lagoon area, as reported in this paper. The studied area is  intensively cultivated and situated in one of the most populated and industrialised regions. Most of the sampling sites are located less than 40 km from the industrial and urban area. Several industries still emit considerable amounts of various elements into the atmosphere. Therefore, contamination could explain part of the enrichment of the surface horizons, al least for some elements. The concentration values for most of the trace elements (e. g. As, Cr, Cu. Hg, Zn) are higher in  urban soils than in undisturbed and reference sites. Iron and Mn are higher at the lagoon inner margin than at the outer margin, , suggesting that oxidation-reduction status plays a significant role in their mobility.

Table 12 - Mean values (mg/kg) of microelements in soils and lagoon sediments at selected sites (data processed from Argese and Bettiol, 2001; Bernardello et al., 2006; Pavoni et al., 1992; Scazzola et al., 2004; Ungaro et al., 2008; Zonta et al., 2007).
                                         
	Outer border	Central lagoon	Inner margin	Urban soils	Undisturbed soils	Background (pre-industrial) 	
As	7.1	n.d.	13	19	12	10	
Cd	0.59	1.8	2.0	0.7	0.9	1.0	
Co	5.1	n.d.	3	10	9	15	
Cr	61	66	107	23	17	20	
Cu	14	37	32	41	21	20	
Fe	12421	18375	20385	n.d.	n.d.	20.000	
Hg	0.7	1.7	1.1	0.1	0.04	0.1	
Mn	237	341	361	n.d.	n.d.	250	
Ni	31	32	50	21	20	20	
Pb	19	78	40	45	53	25	
Zn	71	167	255	95	73	70	

Comparing the relative contribution of the three main sources of contaminants (industry, agriculture, atmosphere), the industrial area of Porto Marghera is still the primary source for Cd (68%) and Hg (39%), and the second source for Ni (31%) and Zn (32%), as stated also by Bellucci et al. (2000) and Critto et al. (2005). The origin of Cd, as well as Zn, Co and Cu, is related to the production of metallic zinc from the mineral sphalerite processing (1936-1978) in industrial plants of Porto Marghera (Pavoni et al., 1987).
Mercury is considered one of the most potentially harmful elements in environmental (particularly aquatic) ecosystems, due to its high toxicity, the potential to accumulate to high levels in aquatic organisms, and therefore the impact on the human health. The average concentration found in the sediments of the Venice Lagoon is 0.6 mg/kg (Zonta et al., 2007). Its concentration at contaminated sites in the lagoon ranges between 40 and 500 mg/kg total Hg. However, no correlation was found between high levels of historical Hg contamination and organism MetylHg concentrations (Bloom et al., 2003). 
Instead, the highest relative inputs for As (91%), Cr (77%), Cu (65%), Ni (56%) and Pb (61%) come from the drainage basin, and are related to their geochemical affinity and to the mineralogical composition of soils and sediments. Arsenic has been already discussed as accumulating by primary geogenic origin, followed by agrochemical input (Ungaro et al., 2008). Arsenic, as well as Hg, is an element of major environmental concern, due to its toxicity and potential to accumulate in living organisms. High As concentrations were found in algae and mussels living in the Venice lagoon (Argese et al., 2005). Total As concentration in Ulva lactuca and Mytilus galloprovincialis ranged from 10 mg/kg  to almost 30 mg/kg (mean 30mg/kg and 22 mg/kg, respectively), with a significantly greater accumulation in the mussels digestive gland, where As content achieved 75 mg/kg. Moreover, As is present in mussels predominantly in the organic and less toxic forms (Argese et al., 2005).
Chromium and Ni accumulation is likely related mostly to their geogenic origin (Cr 77%, Ni 56%). These metals are probably conveyed to the lagoon by runoff water from the drainage basin, or are released from fine particle lagoon muds during erosion and re-suspension consequent to clam harvesting (Sfriso et al., 2005). A second source for Cr (13%) and Ni (31%) is that these metals are typically related to emissions of metal processing manufacturers. Metallurgy contributes Cu (16%) and Zn (32%), which are components of alloys. Traffic is a further important source of Cu, Zn, Pb. Lead was an indicator of traffic emissions in former times since Pb was added to fuel as an antiknock (Norra et al., 2006), and it is likely the present high Pb concentrations to be due to its low mobility. 
The high relative input of Cu (65%) comes from runoff of agricultural areas, where it is widely used, together with Zn,  against vineyard diseases.

4. Conclusion.

Four different factors are responsible for the fate of trace elements in soils: acidic conditions, redox status, organic matter content and soil solution chemistry.
Acidification: increasing acidic conditions, determined by heavy precipitation occurring in the area, cause the progressive replacement of cations on mineral surfaces by protons; decrease in pH results in increased Cu, Zn, Cd and Pb mobilization and accumulation at rangeland and forest sites.
Redox status: oxidation-reduction seems to have a noticeable effect on the distribution of some elements, like Fe, Mn, As. Oxidizing conditions determine precipitation of hydrous oxides, and increased metal sorption capacity (e.g. Cd, Co, As); conversely, reducing conditions cause dissolution of hydrous oxides, liberation of adsorbed metals and release of elements (e.g. Fe, Mn, Co, Cr, Ni) from the soil.
Organic Matter: increased concentration of organic complexing ligants from litter decomposition, plant root exudates and sewage sludge application is the major cause of metal accumulation in surface horizons, especially Cu and Zn at agricultural sites, Pb and Cd at forest sites.
Pore solution chemistry: changes in the ionic composition of the soil solution accounts for competition at sorption sites (e.g. Zn inhibits Cd adsorption), and for the formation of soluble or insoluble compounds. Moreover, a geological matrix effect must be accounted for metal release by hydrolysis of parent material and accumulation in soils (e.g. Ni, Cr, As, Fe, Mn from silicate minerals, Cd from limestone).
Several of the above mentioned mobilization mechanisms are interlinked. For example, oxidation of insoluble sulfide minerals leads both to an increase in acidification by sulfuric acid formation and to the liberation of cations, particularly As (Mascaro et al., 2000). Likewise, the decomposition of freshly incorporated litter and soil organic matter, accompanied by the formation of low molecular weight organic acids, contributes to leaching of metals (e.g. Fe, Mn) down the soil profile in a chelate form, and influences the soil evolution, through the podzolisatios process.
From the soil, trace elements move to surface and groundwater, and through water to the lagoon, where they are concentrated in sediments, or transferred to organisms.
The group of elements with the lowest relative  mobility (bioavailability) includes Co, Cr, Hg, Pb,  As; intermediate elements are Cu, Ni, and the most bioavailable are Zn and Cd.
The level of contamination of the soils investigated is low to moderate, with only some hotspots. Soil heavy metal concentrations are generally within the regulatory guidelines. Exception to this trend is given by anthropogenic Cu and Zn and some As at agricultural sites, and by natural enrichment of As, Ni, Cr. The concentration values for most of the trace elements are higher in both the agriculture and urban sites than in forest sites. The recorded accumulation of Pb and Cd  at forest sites is probably related to acidic precipitation which affected the investigated areas. However, the geological matrix effect must be summed to that of anthropogenic contribution.

Pollution sources could not be detected with certainty at present. Metal concentration decreases with increasing distance from the lagoon, and there are differences between undisturbed, agricultural and urban soils. Surface horizons are enriched with Pb, Cu, Cd, Hg, and this enrichment coincides with an enrichment in soil organic matter, suggesting Pb and Cu to enter, at least in part, the biogeochemical cycle; conversely, Cd and Hg should be introduced in the environment by human activities. This is in agreement with the scheme proposed by Sterckeman et al. (2004) for heavy metals in undisturbed soils: the anthropogenic elements at surface are more likely to be bound to organic matter, while the geogenic elements would mainly be associated with silicates and Fe oxy-hydroxides, with a sensitivity to redox conditions. 

Comparison of the correlations enables inferences concerning the interactions of trace elements with soil properties. This allows a first explanation of the distribution of heavy metal contents in soils. Metals are essentially associated with the soil organo-mineral fraction in the surface horizon, and have positive correlation with soil properties like clay and CEC, and negative correlation with sand, suggesting a lithogenic origin (i. e. they are pedogeochemical fingerprints). 
Principal component analysis supports the differentiation between lithogenic and anthropogenic origin of trace elements, and the association between metals and fine-size grains, and that of Pb with organic matter,  is evident in  the principal components of PCA of both agricultural and forest soils. The positive loadings for most metals on PC1 indicate that this component is associated with a lithogenic origin, and the negative loadings of bioavailable metals at agricultural sites may  be considered as an index of overall contamination of anthropic origin.

The lagoon acts as a sink where heavy metals contributed by agricultural land or originated by waste disposal or by industrial emissions and atmospheric deposition, are conveyed. The ultimate fate of heavy metals, therefore, is to contribute substantially to the lagoon and sediment pollution, and pose environmental hazard for living organisms, including humans. 
The ecological risk as expressed by the hazard quotient (HQ = metal in organisms/metal in soils or sediments) posed by single elements is little for As (HQ  <2 at Porto Marghera, <1.5 in central lagoon; <1 on the mainland, on the basis of 10 points), although at some places its concentration is higher than the regulatory threshold, and very high for Hg and Cd (HQ  <2.5 in central and outer border, <2 in the inner margin).
The cumulative toxic risk for As+Cd+Hg (+Zn) ranges between 6 and 9 toxic units at some hot spots in the central and southern lagoon (between Porto Marghera and Chioggia harbors), indicating a relevant bioaccumulation of trace elements in the lagoon ecosystem, and ranks <3 at other sites on the mainland.
In conclusion, the investigation of soils of the Venice lagoon watershed and the conterminous areas provides valuable information for a comprehensive environmental assessment. Contamination is a major concern to the lagoon, and is probably a residual effect of severe historical inputs since the ‘50s. Instead, on the mainland slight diffuse contamination occur, ant is likely due to anthropic as well as lithogenic origin. 

Acknowledgements
The Environmental Protection Agency of the Veneto Region (ARPAV) is kindly acknowledged for providing agricultural soils sampling and laboratory analyses. Data processing was carried out by G. Camici at the Dept of Physics, University of Florence. S. Gemignani helped in laboratory analyses and computer processing of forest soils data, at the Dept. of Environmental Sciences, University of Venice. 

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Reviewed by J. Bech Borras, Chair of Soil Science, University of Barcelona, Spain.

Caption to figures

Fig. 1 – Location of the investigated region. Inset: the Venice Lagoon watershed and conterminous areas.

Fig. 2 – Sketch diagram of the distribution of agricultural soils as taxonomic USDA orders.

Fig. 3 – Spatial distribution of As concentration in agricultural soils of the Venice lagoon watershed, with indication of the concentration classes.

Fig. 4 - Spatial distribution of Zn concentration in agricultural soils of the Venice lagoon watershed, with indication of the concentration classes.

Fig. 5 - Spatial distribution of Pb concentration in agricultural soils of the Venice lagoon watershed, with indication of the concentration classes.

Fig. 6 – Distribution of variable loadings of agricultural soils in the scatterplot of principal components 1 and 3.

Fig. 7 – Soil horizon differentiation and spatial distribution in the scatterplot of principal components 1 and 3 of agricultural soils. O, A, B, C, are symbols for the regular succession of pedogenic soil horizons; discontinuity marks a difference between surface and subsurface horizons within the soil profile.

Fig. 8 – Spatial distribution of soil samples in the scatterplot of principal components 2 and 3 of agricultural soils, according to the different USDA Soil Taxonomy subgroup level, as revealed by specific soil features.

Fig. 9 – Sketch diagram of the distribution of rangeland and forest soils as taxonomic USDA great groups.

Fig. 10 - Spatial distribution of soil samples in the scatterplot of principal components 1 and 2  of rangeland and forest soils (rotated varimax raw), with indication of different soil groups. 
A, B, C are symbols for soil horizons. 
Numbers represent different soil groups, as follows:
1: calcareous soils (Rendolls, Hapludolls);
2: brown soils (Eutrudepts, Udorthents);
3: leached soils (Paleudalfs);
4: Brown acid soils (Dystrudepts);
5: Podzolic soils (Spodosols).

Fig. 11a: Distribution of variable loadings of rangeland and forest soils in the scatterplot of principal components 1 and 3 (rotated varimax raw), with indication of the main pedogenic processes as revealed by different variables aggregation.
Fig. 11b: Spatial distribution of soil samples in the scatterplot of principal components 1 and 3  of rangeland and forest soils (rotated varimax raw), with indication of different soil groups. Symbols are as in Fig. 10.

Fig. 12a - Distribution of variable loadings of rangeland and forest soils in the scatterplot of principal components 2 and 3 (rotated varimax raw), with indication of the main pedogenic processes as revealed by different variables aggregation.
Fig. 12b - Spatial distribution of soil samples in the scatterplot of principal components 2 and 3  of rangeland and forest soils (rotated varimax raw), with indication of different soil groups. Symbols are as in Fig. 10.

Fig. 13 – Tree diagram illustrating the clustering of different soil horizons according to their similarity. Symbols are as in Fig. 10.