Trace metals, peroxidase activity, PAHs contents and ecophysiological changes in Quercus ilex leaves in the urban area of Caserta (Italy)

Journal of Environmental Management 113 (2012) 501e509

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Trace metals, peroxidase activity, PAHs contents and ecophysiological changes in Quercus ilex leaves in the urban area of Caserta (Italy) S. Papa*, G. Bartoli, F. Nacca, B. D’Abrosca, E. Cembrola, A. Pellegrino, A. Fiorentino, A. Fuggi, A. Fioretto Dipartimento di Scienze della Vita, Seconda Università di Napoli, Via Vivaldi n
43, 81100 Caserta, Italy

a r t i c l e i n f o

a b s t r a c t

Article history: Received 1 September 2009 Received in revised form 25 December 2011 Accepted 30 May 2012 Available online 4 August 2012

Trace metals and polycyclic aromatic hydrocarbons, severely affecting human, animal and plants health, highly contribute to the air pollution in urban areas mainly due to car traffic. In this study the air biomonitoring of the city of Caserta (South Italy) has been performed by using Quercus ilex L., a widespread ornamental plant in parks, gardens and avenues. The plant leaves from different sites within the urban area were collected and used to determine the concentrations of V, Cd, Cr, Pb, Ni, Cu, and PAHs as well as the free amino acid content and peroxidase enzyme activity as indices of the leaf physiological conditions. All the tested trace metals showed concentrations higher than the control site. Lead was positively correlated to Cd and Cr and showed, also, a positive trend with Ni and Cu that, in their turn, were highly correlated between them. Positive and significant correlations were evidenced between total PAHs and carcinogenic PAHs and negative correlations between those and all trace metals assayed except V. Cu and Cd contents evidence negative correlations with peroxidase activity, and the free amino acid contents. The PAHs, in particular Carc-PAHs, were negatively correlated to the tested heavy metals. POD was positively correlated only with V and negatively correlated with Cu and Cd. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Trace elements PAHs Amino acid contents Peroxidase Quercus ilex leaves Urban area

1. Introduction Increased urbanization and industrialization, the rapid growth of population and transport services have altered the air quality. Recently, the researches on air pollution are focused on biomonitoring that is an appropriate means to detect and monitor air pollution effects on organisms. In particular, plant, due to their wide surface distribution and specific responses, can function as pollutant bioindicators and bioaccumulators (Mingorance and Oliva, 2006). Therefore, the tree leaves are very efficient in trapping atmospheric particles and have a special role in reducing the level of “high risk” respirable fine particulates that cause serious human diseases (Tomasevi c et al., 2008; ISO Convention, 1994). The trace metals, emitted from anthropogenic source (industrial plants, power stations, domestic heating systems, motor vehicles), affect leaf elemental composition, enzyme activities and, at the end, plant metabolism and physiology (Alfani et al., 2000; MacFarlane and Burchett, 2001; Hall and Williams, 2003; Ogony Odiyo et al., 2005). Many studies reported that enhancement of leaf

* Corresponding author. Tel.: þ39 0823 274563; fax: þ39 0823 274571. E-mail address: [email protected] (S. Papa). 0301-4797/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jenvman.2012.05.032

peroxidase activities in urban environments with polluted air by intense car traffic (Pulcinelli et al., 1998; Manes et al., 1987, 1989). In addition plants, in polluted air, often synthesize a set of metabolites, particularly specific free amino acids, such as proline and histidine (Sharma and Dietz, 2006). Polycyclic aromatic hydrocarbons (PAHs), deriving from incomplete combustion or pyrolysis of organic material, even if ubiquitous in the global environment, are typically more concentrated in the urban centers (Hyötyläinen and Oikari, 2004). PAHs, mainly coming from cars, refineries and power plants (Srogi, 2007), have received increased attention in air pollution studies because some of them, particularly benzo(a)pyrene, are highly carcinogenic or mutagenic (Wang et al., 2002; IARC, 1983). In this view, the European Communities Commission (2003) proposed to monitor benzo(a)pyrene in air and establish the limit value of 1 ng/m3. PAHs, occurring both in the vapor-phase and condensed form, are adsorbed to aerosol particles in the atmosphere, are deposited on water, soil and plant foliage. Being their deposition, as that of other pollutants dependent on the concentrations in air (Riederer, 1990), plant leaves are the most convenient passive sample for their monitoring. Although the research effort has led to a greatly improved scientific understanding of the abiotic and biotic effects of environmental pollution many of the biotic effects are still poorly understood. Focusing on Italy, besides, data of air monitoring of

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urban areas are available mainly for the North-Central Italy, only a few concern the Southern Italy. Among these some described the trace element and PAHs accumulation in the oak leaves of Naples (Alfani et al., 2000, 2002, 2005, De Nicola et al., 2005, 2008); on the other end the data on the relationship between trace metals, PAHs accumulation and plant metabolism are missing. So the aim of this study was to evaluate the contamination level within the urban area of Caserta (Southern Italy) by investigating the accumulation of both trace elements (V, Cd, Cr, Pb, Ni, Cu) and PAHs on the

Quercus ilex L. as well as the changes in the free amino acid contents and peroxidase activities (POD). In particular the following questions will be investigated: a) Do all parameter tested at each site identify a clear “pollution signal”? b) Do all sampling sites show toxicity symptoms including POD activity and free amino acid contents, compared to the control sample?

Fig. 1. Map of sampling location.

S. Papa et al. / Journal of Environmental Management 113 (2012) 501e509

503

Table 1 Characteristics of the sampling sites and daily average of traffic flow (average of the sampling). Sampling sites

Characteristics

Traffic intensity

Traffic flow (vehicles/h)

JH

High traffic road connecting the city with neighboring countryside near several public offices and railway station and near an underpass. Site along a road where the presence of several traffic lights causes the momentary stop of vehicles. Site located in a residential area, not in direct contact with urban roads with high traffic and not far from the highway. Site located in an area surrounded by tall buildings (>18 m) away from vehicular traffic but near to a cement factory. Site located near the variant intersection that connects the Caserta city to neighboring countryside near building sites and under an overpass. Site located near an area with high traffic, densely populated and adjacent to a gas station and a cement factory. This site, WWF Oasis “Bosco di S. Silvestro” (BSS), is near the city but away from the urban center, and so from anthropogenic sources of pollution. It is located north of the city at 200 m a.s.l. and on 76 ha of area.

Very high

1100

S5 S1 S12 S14 SE Control

2. Material and methods 2.1. Site description The city of Caserta is situated on the Eastern edge of the fertile plain of Campania Region. Its territory covers an area of 54 km2 with a population of 75,208 inhabitants and a density of 1395/km2. The city of Caserta is main town of province and is center of offices and so to local traffic is added to that of borderland. The attention was focused on the city area (“URBAN II”), covering 3.37 km2, with a resident population of about 23,000 inhabitants. Six sampling sites has been selected along roads with different car traffic density (Fig. 1) and compared to the extra-urban site (control site). This site, located in the WWF Oasis “Bosco di S. Silvestro” (41
060 E 14
170 E), is near the city but away from the urban center, and so from anthropogenic sources of pollution. It is 200 m above sea level with a North exposure respect to the city and the vegetation is mostly Q. ilex L. Further details on soil characteristics and biological activity are given in Papa et al. (2002). Tables 1 and 2 show the characteristics of the sampling sites and meteorological data (rain and wind direction) during the experimental period, respectively. 2.2. Sample collection and preparation Leaf samples were collected in November 2005 and May 2006. At each site, the leaves of the previous vegetative season (w18 and 12 months old), were collected around the canopies from three different branches, in order to obtain three sub-samples separately processed. The leaves were cleaned by a brush taking away small spider webs or aphids and a homogeneous part of the sample was kept cool for the enzymatic assay, amino acids and PHAs, while the remainder was dried at 75
C for the element analysis. 2.3. Analytical methods 2.3.1. Chemical parameters The total V, Cd, Cr, Pb, Ni, Cu contents were determined on aliquots (250 mg) of oven-dried (75
C) leaf samples ground to Table 2 Meteorological data (rain and wind) during the experimental period. Sampling

Autumn

Spring

Months old of leaves Total precipitation (mm) Average monthly Months to rainfall above 100 mm (rainfall amount) Prevailing wind direction

w18 2037.5 101.9 10 (159 mm/month)

w12 1164.4 89.5 5 (147 mm/month)

NEeSW

NEeSW

High

836

Low

369

Low

247

Mediumehigh

612

High

856

e

e

a fine powder by an agate pocket (Fritsch Pulverisette type 00.502, Oberstein, Germany) and mineralized using a combination of hydrofluoric and nitric acid (HF 50% v/v: HNO3 65% v/v ¼ 1:2) in a micro-wave oven (Milestone e mls 1200 e Microwave Laboratory Systems) (Papa et al., 2010; Alfani et al., 2000). The concentration of each element was measured by atomic adsorption spectrometry (SpectrAA 20 Varian) via graphite furnace. Accuracy was checked by concurrent analysis of standard reference materials (SRM) from the National Institute of Standards and Technology, Gaithersburg, USA; the recovery ranged from 90 to 100%. For the PAHs analysis, aliquot of fresh leaf samples (w3 g weight) were extracted in 50 mL of acetone for 1 h, subsequently, the leaves were recovered by filtration in vaccum and the extracts were stored in flasks. The recovered leaves were reextracted for 4 h first, by adding 50 mL of acetone, and then over night with further 50 mL of acetone. At the end of each extraction the leaves were recovered by filtration in vaccum and the extracts were stored in flasks. The extracts obtained from each sample were joined together and concentrated to 30 mL volume with a rotary evaporator. 50 mL of water was added to the solution and the mixture was extracted, by liquideliquid extraction, with 50 mL of methylene chloride(two times), obtaining an organic (fraction A) and an aqueous fraction (fraction B). The organic fraction, dried with Na2SO4, was concentrated under vacuum and re-dissolved with 25 mL of npentane. The obtained solution was shaken with dimethylsulfoxide (25 mL) in a separatory funnel. To the organic solution, 75 mL of water was added and the mixture was shaken in a separatory funnel with 50 mL of cyclohexane as extracting solvent, obtaining an organic (fraction A) and an aqueous fraction (fraction B), this latter was dried with Na2SO4 and concentrated under vacuum until 1 mL. The cyclohexane extract was purified by chromatography on Florisil eluting with 3 mL of a cyclohexane: methylene chloride (1:1) mixture. The qualitative and quantitative determinations were carried out by means of a gas chromatograph (HP 6890 PLUS instrument in split mode with a flame ionization detector.) GC separations were achieved on a Zebron ZB-5ms (30 m, 0.25 mm id, 0.25 mm) fused-silica capillary column from Phenomenex (Torrance, CA). The column oven was increased by 155e260
C at 25
C/min, then to 280
C at 25
C/min, finally to 320
C at 25
C/min for 2 min; injector temperature was 285
C, while the carrier gas was He, and the flow rate was 1.4 mL/min. The PAHs were identified by comparing their retention times with those of a certified standard mixture (Ultra Scientific 610 PAH Calibration Mix B).

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The following 16 compounds were quantified through a calibration curve: Acenaphthene, Acenaphthylene, Anthracene, Benz[a]anthracene, Benzo[b]fluoranthene, Benzo[k]fluoranthene, Benzo[ghi]perylene, Benzo[a]pyrene, Chrysene, Dibenz[a,h]anthracene, Fluoranthene, Fluorene, Indeno[1,2,3-cd]pyrene, Naphthalene, Phenanthrene, Pyrene. The accuracy of the analytical procedure was checked by adding to the samples surrogate standard 1-fluoronaphthalene, (purity >99%) prior to extraction. Average recovery calculated is 83%. The analytical LOD values were 10 ng/g. 2.3.2. Enzyme extraction and assays Peroxidase activity (POD) was determined, on aliquot of fresh leaves (50 mg) powdered in liquid nitrogen, (Fioretto et al., 2000) adapting previous protocols (Leatham and Stahamann, 1981; Ander and Eriksson, 1976). The activity was expressed as mmol of o-tolidine oxidized h1 g1 of leaf d.w., using as the molar extinction coefficient at 600 nm of oxidized o-tolidine of 6340 (McClaugherty and Linkins, 1990). 2.3.3. Amino acids analysis Amino acids were extracted and determined according to Carillo et al. (2005). Briefly free amino acids were two fold extracted with ethanol:water (40:60 v/v) from aliquot (50 mg) of fresh leaf samples powdered in liquid nitrogen, centrifuged at 14,000 g for 5 min. The primary amino acids in the collected supernatants were derivatized by o-phthaldialdehyde (OPA), separated by high-performance liquid chromatography and detected fluorometrically. The identification was performed by treating amino acid standards as the leaf samples.

2.4. Statistics All the analyses were performed in triplicate for each leaf sample and expressed as mean  SD. Correlations between parameters were calculated using the simple Pearson correlation coefficient. The significance of differences was tested by two-way analysis of variance (ANOVA) followed by Tukey test (MINITAB INC 13). In order to examine the overall relationship between the parameters the data were also analyzed by Principal Component Analysis, (PCA, SYN-TAX 2000). Differences were considered to be significant at p < 0.05 level of significance.

3. Results The metals contents (mg/g d.w.), differed among the sites and between the sampling times (Fig. 2). The trace metals in the urban sites largely exceeded (p < 0.001) their content in the control site (BSS). By comparing the two sampling, in this site (BSS), the significantly higher concentrations were determined in the spring sampling (p < 0.01). Cd and Pb leaf contents were generally higher in the spring than the autumn sampling in all sites; only exception for Cd in the S12 where no significant differences in the two sampling data were found. Besides, the leaf contents of Cu and Ni, measured in the two sampling data, did not significantly differed in all sites. For the other metals, instead, the data obtained were heterogeneous, in particular JH showed, in autumn, a higher concentration of V and Cr. For the other sites, there weren’t significant differences between sampling data, except S5 in spring; moreover, JH showed, in

Fig. 2. Metals contents (mg/g d.w.) measured in Quercus ilex leaves from urban sites in autumn (A) and spring (S). Different letters show significant differences between the sampling at least p < 0.05.

S. Papa et al. / Journal of Environmental Management 113 (2012) 501e509

autumn, a higher concentration of Cr, instead S5, SE and S1 showed a higher concentration of Cr in spring. By comparing the traffic flow (Table 1) with trace metal contents in all sites (Fig. 2) it was observed that the sites with a high traffic flow were more polluted by trace metal than the others; in fact S12 with a low traffic flow showed lower Pb, Cd and Cr contents. The degree of heavy metal pollution in the leaf samples of Q. ilex was also evaluated by using the Pollution Load Index (PLI) (Ahmad et al., 2007). This index is based on the values of the Concentration Factors (CF) of each element in the sample. The CF is the ratio obtained by dividing the concentration of each element in the sample (Csample) by the concentration of the same element obtained at reference sites (Creference). The PLI for each element at the respective site was calculated as the nth root of the product of the n CF values. This index provides a simple, comparative means to assess the level of elemental pollution. Values of PLI close to 1 indicate that elemental loads are near to the background level, and values above 1 indicate the extent of pollution. The average values of each element at the respective sites were used for such calculations and the results were reproduced in Fig. 3. The higher PLI for Pb could be attributed to vehicular traffic. In fact the exhausts of cars contain fractions of this element from antiknock additives and this comes, also, by a rapid wear and tear of the old tyres. The elevated PLI for Cu, V, Cd and Cr could probably be due to the presence of heterogeneous sources: an industrial area, an operative cement factory, a railway station, a street with high vehicular traffic and of a some road maintenance which contribute these alloy forming metals to the environment. The PLI evaluated for site (Fig. 3) showed, in spring, that only the S12, with a lower vehicular traffic, appeared less 1; on the contrary, S1, subjected to industrial pollution and highway, had an index w2

Fig. 3. PLI for each element and for each urban site in autumn (A) and spring (S) using biomonitors.

505

Fig. 4. Total and carcinogenic PAH concentrations measured in Quercus ilex leaves from the urban sites in autumn (A) and spring (S). Different letters show significant differences between the sampling at least p < 0.05.

and the others, subjected to medium and high vehicular traffic showed a PLI range between 2 and 3. In autumn the PLI was above 1but lower than spring as a consequence of high precipitations. SE site showed the lowest PLI as metals. Also the total PAH concentrations exceeded the values of control site (BSS) (Fig. 4) (p < 0.001). The occurrence of PAHs in control site is explained mainly by aerial transport from distant anthropogenic sources and also by the presence of conifers nearby. The total PAH concentrations ranged from 1.27 to 3.9 mg/g d.w. (Fig. 4) in autumn and from 1.38 to 3.77 mg/g d.w. in spring and the highest concentrations were found in S1 and S12 sites, situated at SW and NE of Caserta city, respectively, in the direction of prevailing winds. Carcinogenic PAHs (IARC, 1983) (Fig. 4) showed similar trends as the total PAHs except S1 site, where we observed lower carcinogenic PAHs than the total (33% of the total). This site, in fact, was subjected to a different source pollution due to the proximity of the motorway, metallurgical and engineering industries and as a consequence we found a PLI > 1. S12 site, instead, still showed the highest values (57% of the total). This site was subjected to the pollution of cement plant, quarries and gas turbine power plant, and since this pollution is linked more to the PAHs than metals the PLI was <1. The total PAHs were grouped into low (LMW), medium (MMW) and high (HMW) molecular weight according to Harner and Bidleman (1998) (Fig. 5). This subdivision was based on their air partitioning between particulate and gaseous phase: 1) LMW, PAHs that exist mostly in the gaseous phase; 2) MMW, PAHs that partition between particulate and gaseous phases depending on the environmental conditions; 3) HMW, PAHs exist mostly in the particulate phase (Jouraeva et al., 2002). So, LMW and MMW are generally transported long distance respect to HMW. In this study, we observed that the MMW and HMW PAHs contributed 44% and 35% to the total respectively, whereas LMW PAHs contributed the lowest percentage to the total (20%). As is well known, PAHs formed during in combusting of organic materials, including oil derivates, coals, natural gas, biomass, etc.

506

S. Papa et al. / Journal of Environmental Management 113 (2012) 501e509 Table 3 Free amino acid contents (mmol g1 d.w.) in Quercus ilex leaves of the urban sites in autumn (A) and spring (S). The values are mean  15% S.D.

Asp Glu Asn Ser His Gln Gly Thr Arg Ala Tyr Gaba Trp Met Val Phe Ile Leu Lys

Fig. 5. LMW, MMW and HMWPAH concentrations measured in Quercus ilex leaves from the urban sites in autumn (A) and spring (S). Different letters show significant differences between the sampling at least p < 0.05.

The higher values of HMW were found in S1 and S12 sites (Table 1) than the others (Fig. 5). This result showed that in the sites close to emission source were dominant HMW, while in the sites away from them LMW prevailed. The free amino acid contents (Table 3) did not show significant changes between the autumn and the spring samplings in all the sites. Only Glutamate and glutamine significantly changed. In fact depending of their central role in nitrogen assimilation and transport they are very sensitive to the physiological status of the leaf. Among the free amino acids that did not suffer changes in the leaves, significant differences were observed among the sites. In particular, the JH and S5 sites showed the highest and the lowest concentration of asparagina, respectively (p < 0.01). Tryptophan (trp) and methionine (met) showed the lowest and the highest contents in JH and S5 sites, respectively (P < 0.001). Tyrosine (tyr), threonine (thr), isoleucine (ile) and lysine, did not showed significant differences among the sites. Glycine (gly) and serine (ser) had lower values in the S1 site (P < 0.01). The peroxidase activity (POD) (Fig. 6) in the leaves of city sites as for metals, exceeded the values found in the control site (BSS) and varied with the sampling seasons. In particular, it was generally higher in autumn, subjected to prevailing winds from SW and NE, than in spring, with winds from NE. The highest values were evidenced in the JH site (Table 1). Il JH was a particular site because it

A S A S A S A S A S A S A S A S A S A S A S A S A S A S A S A S A S A S A S

SE

JH

S5

S1

S12

S14

3.99 3.87 5.58 2.31 0.30 0.27 2.07 1.98 0.48 0.57 2.37 0.81 0.75 0.75 0.48 0.48 0.72 0.18 1.29 1.23 0.42 0.45 0.27 0.18 0.99 0.96 0.15 0.15 0.36 0.33 0.72 0.12 0.24 0.24 0.45 0.45 0.48 0.33

4.62 4.44 6.33 2.31 0.63 0.60 1.47 1.11 0.30 0.30 1.98 1.11 0.81 0.78 0.42 0.42 1.17 0.96 1.32 1.26 0.42 0.39 0.30 0.30 0.18 0.18 0.15 0.15 0.33 0.33 0.24 0.45 0.21 0.21 0.24 0.24 0.57 0.57

1.26 1.2 2.43 2.61 0.09 0.09 0.84 2.01 0.18 0.15 0.81 0.63 0.75 0.72 0.45 0.42 0.33 0.27 0.66 0.63 0.33 0.42 0.15 0.18 0.45 0.75 0.09 0.09 0.24 0.21 0.21 0.21 0.18 0.18 0.15 0.15 0.33 0.33

3.24 3.12 5.73 2.46 0.15 0.15 0.78 0.75 0.15 0.24 0.99 0.69 0.42 0.42 0.36 0.33 0.24 0.57 1.08 1.05 0.27 0.42 0.24 0.15 0.78 0.75 0.12 0.12 0.39 0.36 0.15 0.24 0.18 0.18 0.21 0.21 0.27 0.27

1.41 1.44 2.1 2.16 0.12 0.12 2.31 2.28 0.21 0.21 0.54 0.51 0.81 0.84 0.36 0.33 0.15 0.18 1.41 1.41 0.45 0.45 0.21 0.21 1.02 1.08 0.12 0.12 0.42 0.39 0.21 0.21 0.27 0.27 0.51 0.51 0.27 0.27

3.03 3.06 2.58 2.64 0.36 0.33 0.75 0.75 0.24 0.24 0.75 0.78 0.39 0.42 0.54 0.54 0.63 0.66 1.05 1.02 0.45 0.45 0.12 0.15 0.69 0.72 0.15 0.15 0.39 0.36 0.15 0.15 0.18 0.18 0.18 0.18 0.24 0.24

was near an underpass with a high traffic vehicular, rail and bus station and, it was, also, located near the outdoor court yard of the Royal Palace that didn’t allow the dispersion of pollutants. In order to propose the possible sources of these metal contaminants in the vegetation samples, it has been determined the correlation among the different parameters assayed (Table 4). In particular, the correlation analysis among metals may suggest a possible common origin in the case of positive relationships and

Fig. 6. Peroxidase activity (POD) (mmol h1 g1 d.w) in Quercus ilex leaves from urban sites in autumn (A) and spring (S). Different letters show significant differences between the sampling at least p < 0.05.

S. Papa et al. / Journal of Environmental Management 113 (2012) 501e509

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Table 4 Correlation between heavy metals, POD and PAHs in Quercus ilex leaves of the urban sites.

V Cu Cd Ni Cr Pb POD Tot PHAs Carc PHAs PAH LMWs PAH MMWs PAH HMWs

V

Cu

Cd

Ni

Cr

Pb

POD

Tot PAHs

Carc-PAHs

PAH LMWs

PAH MMWs

NS() NS NS NS NS 0.71*** NS NS 0.36* NS NS()

0.54*** 0.58*** 0.43** NS(þ) 0.37* 0.72*** 0.66*** 0.61*** 0.66*** 0.43**

0.50** 0.48** 0.67*** 0.49** 0.44** 0.43** 0.36* 0.66*** NS

0.45** NS(þ) NS 0.76*** 0.39* 0.52*** 0.63*** 0.67***

0.33* NS() 0.42** 0.52*** 0.38* NS() 0.45**

NS() 0.37* 0.596 0.53*** 0.66*** NS

NS() NS() NS() NS 0.33*

0.83*** 0.81*** 0.88*** 0.72***

0.79*** 0.77*** 0.49**

0.77*** 0.41**

0.32*

NS not significant; *P < 0.05; **P < 0.01; ***P < 0.001.

different emission sources in case of negative relationships. Lead was positively correlated to Cd and Cr and showed a positive trend with Ni and Cu that in turn, were highly correlated between them. Positive and significant correlations were evidenced between total PAHs and Carc-PAHs and negative correlations between those and all trace metals assayed except V (Table 4). LMW PAHs were negatively correlated to all trace metals, MMW PAHs only to Cu, Cd, Ni and Pb and HMW PAHs only to Cu, Ni and Cr. The peroxidase activity was positively correlated only with Vanadium, suggesting that this metal induced a stress state in the plant leaves (Table 4). On the contrary, the POD activity was negatively correlated to Cu and Cd. Highly significant negative correlations between valine and all the tested metals except Cr and Pb and positive correlations with threonine except Pb and Cd (Table 5). Cadmium, Cr and Cu showed negative significant correlations with alanine. Glutamate was positively correlated to V and negatively correlated to Cd, while V and Ni were positively related to lysine, glycine and serine. 4. Discussion The present study analyzed trace metal concentrations (Pb, Cd, Cr, Ni, V and Cu) in the Q. ilex leaves sampled in different sites of urban area of Caserta. Cadmium and Pb leaf contents were generally higher in spring than in autumn. This can be attributed to a wash-out process of metal deposition by rain during the month

before the sampling (Table 2). The elements, in fact, can be taken up via roots from the soil and transported to the leaves, but they may also be taken up from the air or by precipitation directly via the leaves (Rucandio et al., 2010). In this study the leaves sampled in autumn (w18 months old) have been exposed for ten of about 18 months to rainfall above 100 mm (159 mm/month); while those sampled in spring have been exposed for only five of about 12 months to the same amount of rainfall (147 mm/month) (Table 2). Similar results were reported by Fatoki (1996) where lower values were obtained for autumn than spring. Also Lehndorff and Schwark (2010) have observed that the Cd decrease in autumn was correlated to precipitation. The metal concentrations were lower than those reported for other cities (Alfani et al., 2000; Ogony Odiyo et al., 2005; Eboh and Thomas Boye, 2005). In particular, by comparing the data with the Naples, the nearest large town, the metal concentrations assayed ranging from 0.07 to 26.84 mg g1 for Pb, 0.05 to 4.04 mg g1 for Cr, 0.05 to 9.71 mg g1 for V, 6.97 to 51.47 mg g1 for Cu, 0.09 to 4.87 mg g1 for Ni, 0.01 to 0.69 mg g1 for Cd (Alfani et al., 2000). The PAH values are in agreement with those found other Italian cities like Naples and Palermo (De Nicola et al., 2005; Orecchio, 2007). The higher PAH concentrations found in S1 and S12 could be related to the proximity of highway and industrial area and of cement factory, respectively. Therefore, even if the abundant rains (211.6 mm in November) have washed the leaves, it was certainly observed, in all sites, a higher trend of unburned hydrocarbons. This

Table 5 Correlation between trace metals. PAHs and amino acid contents in Q. ilex leaves of the urban sites.

Asp Glu Asn Ser His Gln Gly Thr Arg Ala Tyr Gaba Trp Met Val Phe Ile Leu Lys

V

Cu

Cd

Ni

Cr

Pb

POD

Tot PAHs

Carc-PAHs

PAH LMWs

PAH MMWs

PAH HMWs

0.36* 0.35* 0.54*** NS NS 0.35* 0.36* NS() 0.57*** NS NS 0.47** 0.64*** NS 0.39* NS() NS() NS() 0.64***

NS() NS() NS() NS NS NS() NS 0.51** NS() 0.72*** NS 0.34* NS 0.33* 0.79*** NS 0.31* NS() NS()

NS 0.48** NS() NS() NS 0.33* NS() NS NS() 0.38* NS NS() NS NS() 0.46** NS() NS() NS() NS()

NS NS() 0.40* 0.36* 0.51 NS 0.48** 0.54*** NS NS() 0.39* NS NS() NS 0.47** NS NS NS 0.41**

0.39* NS 0.35* 0.38* NS NS 0.45** 0.71*** 0.34* 0.37* NS 0.33* NS() 0.37* NS() 0.31* 0.58*** 0.52*** NS()

0.50*** NS NS NS() 0.44** NS NS() NS() NS NS() NS() NS NS() NS NS() NS NS() NS() NS

0.60*** 0.74*** 0.66*** NS() 0.196 0.74*** 0.34* NS() 0.67*** 0.36* NS() 0.74*** 0.61*** 0.33* 0.010 0.283 0.069 NS() 0.77***

0.34* NS() NS() NS() 0.71*** 0.45** NS() 0.65*** NS() NS NS() NS() NS NS() 0.50*** 0.47** NS NS() 0.45**

0.44** NS() NS() NS 0.51*** 0.45** NS 0.59*** NS() 0.44** NS NS NS NS() 0.51*** 0.41** 0.45** 0.36* 0.34*

0.34* NS() NS() NS 0.55*** 0.48** NS() 0.37* 0.34* 0.34* NS NS() 0.32* NS() 0.66*** 0.42** NS NS 0.51***

NS() NS NS() NS() 0.676 NS() NS() 0.335 NS() NS NS() NS() NS() NS() 0.480 0.441 NS() NS() 0.327

0.35* 0.31* 0.50*** NS() 0.49** 0.57*** NS() 0.79*** 0.39* NS() NS() NS() NS 0.45** NS NS() NS() NS() 0.46**

NS not significant; *P < 0.05; **P < 0.01; ***P < 0.001.

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increase is probably due to a) poor combustion linked to extremely adverse weather conditions, b) high percentage (60%) of cars with more than 6 years old and motorbike, c) traffic jam due to total clogging of the two main streets of Caserta. Absent of significant correlations between PHAs and V could be depend because V remains in the heavy fraction of fossil fuels in high levels and is placed in the air in large quantities by crude oil combustion, diesel, petrol, oil, coal and lignite. The concentrations of this element in the atmosphere varie widely because of different seasonal conditions (Delbono et al., 2003). Poor combustion, favored by extreme weather conditions, results in a higher concentration of this element in the ashes. Heterogeneous sources of pollutants (motor vehicle traffic, railway, highway, factories, quarries, landfills, cement factory) do not favor a positive correlation between trace metals and PAHs. The correlation between heavy metals and free amino acid suggest that also valine and threonine concentrations are affected by metals and could have a role in their biomonitoring. In fact threonine was positively correlated to V Cd, Ni and Cu, while valine was negatively correlated to them. In particular, higher negative correlation for valine (see Cd) evidenced also negative correlation with leucine and isoleucine. Threonine is an intermediate of the synthesis of isoleucine, whose biosynthesis shares four enzymes with that of valine and leucine (Buchanan et al., 2000). Their biosynthesis is tightly regulated and many enzymes of the metabolic pathways are allosterically regulated. Threonine dehydrase, for example, a key enzyme for isoleucine biosynthesis is inhibited by isoleucine and activated by valine. The negative correlation among the concentration of the tested metals, valine and the other amino acids suggests that such elements can affect enzymes downstream to threonine. The positive correlation between heavy metals and threonine and negative correlation between these and valine can be as a more general plant response to stress conditions, considering that the intermediary compounds of such pathways are involved in the biosynthesis of different secondary plant metabolites (Yakhin et al., 2009; Rossini Oliva et al., 2009). A positive significant correlation between histidine and Ni that was reported also by other authors (Kerkeb and Kramer, 2003; Wycisk et al., 2004). In Ni treated plants, the tissue histidine concentration increases due to its role as nickel chelator (Sharma and Dietz, 2006). Trace metals can cause oxidative stress in plants. In fact the toxic effect of trace metals appears related to their ability to increase the concentration of reactive oxygen species (ROS), and accumulation of

H2O2 (Baycu et al., 2006). In this view, POD was positively correlated only with V, suggesting that this metal induced a stress state in the plant leaves. Several studies have shown that POD in urban environments was higher than in the control sites in relation to the air pollution (Radotìc et al., 2000; MacFarlane and Burchett, 2001; Markkola et al., 2002). On the contrary, the POD activity was negatively correlated to Cu and Cd as reported by Pandey and Sharma (2002) in Brassica species treated with an excess supply of Cd. The similar negative trend was found for PAHs and POD activity (Table 4), probably because the plants is true that posses antioxidant enzymes but these operates either unspecifically or depending on the nature and the level contamination (Dazy et al., 2009). In this way, the negative correlation among POD, trace elements and PAHs suggest that a synergy of abiotic and also biotic factors may have affected the plant responses. The Principal Component Analysis (PCA) evidenced a clear grouping of the sites along axis 2 (Fig. 7): the first group contains S5 and S1 sites (located at SW of Caserta city), the second S14, SE and S12 sites (located at NE of Caserta city) and the third JH site, pointing different source of pollution. S1 and S5, as already mentioned above, were located next to the motorway, metallurgical and engineering industries; S14, SE and S12 were close to cement plant, quarries and gas turbines; JH was a particular site in the center city. Besides, POD activity shows a separation among the sites while the other tested parameters are more close to the origin (Fig. 7), probably pointing a synergistic effect rather than specific for individual pollutants. This could be a further confirmation that the sites are subject to different sources of pollutants. 5. Conclusion This study shows that all parameter tested at each sites identify a pollution signal, linked to different source pollution, and that the comparison with the control site and POD activity appears to be the discriminating factor. On the whole, the data obtained are interesting because they represent the first available data in the city of Caserta and they provide a database allowing the evaluation of environmental pollution. These data can also serve as a starting point for further biomonitoring in the city of Caserta and could be used as preliminary reference set for the evaluation of future trends of these pollutants. Acknowledgments This work was financially supported by “Comune di Caserta” within the Program of Community Initiative “URBAN II” of Caserta (Campania Region e South Italy). We thanks Dr. F. Paolella, for granting permission to work in the WWF “Oasi Bosco di S. Silvestro” and Dr A. Rubino for providing us meteorological data of Caserta city. References

Fig. 7. Biplot resulting from all parameters assayed. Vectors indicate the sampling sites.

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