Atmospheric Environment 42 (2008) 8273–8277 Contents lists available at ScienceDirect Atmospheric Environment journal homepage: www.elsevier.com/locate/atmosenv Long-term monitoring of metal pollution by urban trees Loretta Gratani*, Maria Fiore Crescente, Laura Varone Department of Plant Biology, Sapienza Univerity of Rome, P.le A. Moro, 5 00185 Rome, Italy a r t i c l e i n f o a b s t r a c t Article history: Received 25 February 2008 Received in revised form 14 July 2008 Accepted 21 July 2008 The atmospheric pollution level in Rome was monitored in the year 2006. Five sites in the historical centre were considered. The concentration of Al, Fe, Cu, Zn, and Pb was analysed in washed and unwashed Quercus ilex leaf samples. Moreover, in order to verify the changes in atmospheric pollution in the historical centre of the city after the introduction of the limited traffic zone (LTZ), previous data collected in the years 1979 and 1996 were also considered. The leaf’s internal concentration of Al, Fe, Cu, Zn, and Pb was 28, 22, 40, 77 and 37%, respectively, of the total concentration, and it was in the same range monitored in the years 1979 and 1996. The results underlined a significant (p < 0.05) decreasing of metal concentration on unwashed leaves with on an average 92%, compared to ones monitored in the year 1979. The mean value of the total traffic flow during the limitated period (Monday to Friday, from 6:30 a.m. to 6:00 p.m, and Saturday from 2:00 to 6:00 p.m.) was 75.000 vehicles, compared to 90.000 ones before the electronic gates were activated; moreover, a 15% decrease in the daily traffic peak (8:30–9:30 a.m) was monitored. The metal concentration in Q. ilex leaves was be related to motor vehicle emissions, confirmed also by PCA. The data obtained on the leaf metal concentration trend in Rome, over a period of 27 years, underlined the importance of the City Council provisions. These results confirmed the use of Q. ilex for long-term monitoring of metal concentration in those urban areas where the species was naturally present, and widely distributed in the landscape. Ó 2008 Published by Elsevier Ltd. Keywords: Bio-monitor Metal pollution Quercus ilex Rome Vehicular traffic 1. Introduction Vehicular traffic is one of the major sources of heavy metal contamination, either in soils or roadside dusts in urban areas, and it has increased in the last years (Colvile et al., 2001; Çelik et al., 2005; Ahmed and Ishiga, 2006; Ovadnevaitë et al., 2006). The spatial and temporal distribution of air pollutants within urban areas is crucial to human health (Urbat et al., 2004), since they are readily inhaled by humans (Rossini Oliva and Espinosa, 2007). Nevertheless, many factors influence pollutant concentration in urban areas, including climate, urbanistic characteristics, and both volume and type of the ‘‘green’’. Plants not only have an ornamental function in urban areas, but they may also improve the quality of urban life * Corresponding author. Tel./fax: þ39 06 49912358 E-mail address: loretta.gratani@uniroma1.it (L. Gratani). 1352-2310/$ – see front matter Ó 2008 Published by Elsevier Ltd. doi:10.1016/j.atmosenv.2008.07.032 (Akbari, 2002; Brack, 2002), having a role in carbon dioxide sequestration and oxygen releasing through photosynthesis, contributing to air temperature mitigation by shading and transpiration (Akbari, 2002; Gratani and Varone, 2006). Moreover, plants can uptake and accumulate pollutants through their roots and leaf surfaces (Sawdis et al., 2001); in particular, leaves can act as biological absorbers of pollutants (Gratani et al., 2000; Pal et al., 2002). Particles can be dry deposited on plant surfaces and accumulated through sedimentation under the influence of gravity through impaction resulting from wind (Nowak, 2004). They can also be kept with internal leaf accumulation and/or retention on the leaf surface (Gratani et al., 2000). Atmospheric metal concentration monitoring can be carried out by different types of biological monitors, including plants, fungi, lichens, and tree bark (Capannesi et al., 1981; Gratani and Crescente, 1999; Gratani et al., 2000; Monaci et al., 2000; Pyatt, 2001; Del Rio et al., 2002; Yilmaz 8274 L. Gratani et al. / Atmospheric Environment 42 (2008) 8273–8277 and Zengin, 2004; Madejon et al., 2006; Al – Alawi and Mandiwana, 2007; Rossini Oliva and Espinosa, 2007). Biological monitors are organisms that provide quantitative information on some aspects of their environment, such as how much of a pollutant is present (Martin and Coughtrey, 1982). Moreover, in urban area higher plants are mostly suitable for monitoring metal pollution since as lichens and mosses are often missing (Al – Alawi and Mandiwana, 2007). Alfani et al. (1996), Pyatt (2001), Avila et al. (2003), Urbat et al. (2004), Maisto et al. (2004), Sardans and Peñuelas (2005) underline the use of tree leaves for pollution biomonitoring. The main advantage of the plants use as bio-monitor is that plants are wide-spread providing a high density of sampling points (Moreno et al., 2003). Moreover, the most economical and reasonable method for biomonitoring heavy metal levels in the atmosphere is using plants (Çelik et al., 2005). Among trees, evergreen species are better traps for particles than deciduous ones because of their longer leaf longevity, which can accumulate pollutants throughout the year (Gratani and Varone, 2006, 2007). Thus, information on atmospheric pollution may be deduced from the concentration of specific substances in plant tissues (Wolterbeek and Peters, 2000; Kapusta et al., 2006), offering low-cost information about environmental quality (Çelik et al., 2005; Rossini Oliva and Espinosa, 2007). The main objective of this research was to monitor the atmospheric pollution level in Rome, after the introduction of the limitation traffic zone (LTZ) in the centre of the city, by the City Council. We considered Quercus ilex L., which is naturally present in the Rome landscape; moreover, it is widely distributed since it is furnished for ‘‘green’’ streets in the city. To evaluate the efficacy of this provision we compared the data collected in the year 2006 with those by Capannesi et al. (1981), and Gratani et al. (2000), for the same sites, in the years 1978 and 1996, respectively. Moreover, we would identify the main trend of the data along with the variables, throughout the years, by factorial analysis. value  S.E.), were selected in each of the considered sites. These trees were the same plants investigated in the years 1979 and 1996. Three leaf samples (per tree), of 250 g each, were collected from the south-eastern side of the lower crown portion (according to Capannesi et al., 1981; Gratani et al., 2000), in July 2006, a week after the last rainfall. Leaf samples were stored in polyethylene bags and transferred immediately to the laboratory. Chemical analysis were carried out following the same analytical procedure used by Capannesi et al. (1981), and Gratani et al. (2000), in order to compare the results of 2006 with those monitored in the years 1978 and 1996. Two leaf sub-samples, without petioles, were selected and one of them was washed with deionised water and an aqueous solution of 5% Triton-x100 (Ratcliffe and Beeby, 1980) to remove superficial leaf deposit. Both washed and unwashed leaf samples were oven dried at 90  C to constant mass, and pulverised by a Retsch PMA pulveriser, then Al, Fe, Cu, Zn and Pb concentration was analysed. The concentration of Al, Fe, Cu, Zn, and Pb was analysed in triplicate by flame atomic absorption spectrometry (AAS; maximum versatility 82547), after hashing them in a muffle furnace (Haeraeus). The hashed samples were digested by a hotplate at 80–90  C for 3 h in 20 ml of 1:1 (w/w) (constant boiling) HCl pure water solution, according to Wheeler and Rolfe (1979). The leaf’s internal metal concentration was calculated as the difference between unwashed and washed leaf samples. In order to verify the atmospheric pollution change in the historical centre in response to LTZ, the results were compared with the data previous collected at the same five sites, in the year 1979, before the green fuel and catalytic exhaust introduction (Capannesi et al., 1981), and in the year 1996 (Gratani et al., 2000), when LTZ was active but without electronic gates. 2. Materials and methods 2.3. Statistic analysis 2.1. Study site Statistical significance of the mean values of the metal concentration with respect to the considered years (1978, 1996 and 2006) were analyzed by a one-way analysis of variance (ANOVA), followed by the Tukey test for multiple comparisons. Two Principal Component Analysis (PCA) were used to get associations of metal factors in order to identify their trend in 1979 and 2006. PCA was carried out on the basis of a matrix of the normalised data using unwashed leaf samples. All statistical tests were performed using a statistical software package (Statistica, Statsoft, USA). The study was carried out in the city of Rome, in July 2006. We considered five sites (Popolo Square, Pincio Slope, Cairoli Square, Fori Imperiali Street, Venezia Square) in the historical centre of the city, which have been transformed into a limited traffic zone (LTZ), by the City Council provision since 1989, in order to limit vehicle traffic. This limitation was implemented in the year 2001 by the introduction of electronic gates to control the access. In the LTZ, the traffic limitation during the week was active Monday to Friday, from 6:30 a.m. to 6:00 p.m and Saturday from 2:00 to 6:00 p.m. The five sites had been chosen among those monitored by Capannesi et al. (1981), and Gratani et al. (2000). 3. Results 3.1. Leaf metal concentration 2.2. Chemical analysis Three Q. ilex trees, of comparable size (plant height was 16  1 m and diameter at breast height 50  4 cm, mean The metal concentration of unwashed and washed leaf samples monitored in the years 1979, 1996, and 2006 are shown in Fig. 1A and B. 8275 L. Gratani et al. / Atmospheric Environment 42 (2008) 8273–8277 Ln of metal concentration A 10 Unwashed a a b 8 b c b b a b a 4 c c c 2 0 Ln of metal concentration B 10 Washed 8 1979 1996 2006 a a b b 6 a c c b b a b 4 a c c 2 c 0 Al Fe Pb Cu Zn Fig. 1. Ln of metals concentration in unwashed (A) and washed (B) Q. ilex leaf samples collected in different years (1979, 1996 and 2006) at the same sites. The annual differences in mean values of the metal concentration with different letters are significantly different (ANOVA, p < 0.005 and the Tukey Test for multiple comparisons). Significant differences (p < 0.05) in the metal concentration among the unwashed leaf samples collected in 1979, 1996 and 2006 were found (Table 1). Comparing unwashed and washed leaf samples collected in the year 2006, the leaf’s internal concentration of Al, Fe, Cu, Zn, and Pb was 28, 22, 40, 77 and 37%, respectively, of the total concentration, and it was in the same range monitored in the years 1979 and 1996. On an average, the total leaf concentration monitored in the year 2006 was 92% lower than that monitored in the year 1979. 3.2. Statistic analysis The results of PCA, carried out using data monitored in 1979 and 2006, showed two factors explaining the variation of the metal concentration for the considered years (Table 2). Factor 1 accounted for 49% of the total variance in 1979, and it was significantly correlated to Pb and Zn, while Table 1 Results of ANOVA Metals Al Fe Table 2 Factors loadings for PCA of metal content in Q. ilex unwashed leaf samples carried out using data collected in the years 1979 and 2006 Metal a c 6 1979 1996 2006 Cu Zn Pb Degrees of freedom 2 2 2 2 2 F values 5.3 10.9 7.0 4.8 16.4 Observed p values 0.0084* 0.00015* 0.0023* 0.013* 0.000005* *Significant difference among the samples collected at the same sites in 1979, 1996 and 2006 (at p values < 0.05). Al Pb Fe Cu Zn Eigen values % Of explained variance 1979 2006 Factor 1 Factor 2 Factor 1 Factor 2 0.213 0.915* 0.269 0.490 0.895* 2.4 49 0.811* 0.165 0.850* 0.463 0.263 1.3 25 0.963* 0.179 0.935* 0.076 0.082 2.0 41 0.135 0.731* 0.253 0.752* 0.756* 1.6 31 *Statistically significant (p > 0.7). In the year 1979 Factor 1 accounting for the most of the total variance (49%) was significantly correlated to Pb and Zn. In the year 2006 Factor 1, explaining the most of the total variance (41%) was significantly correlated to Al and Fe. Factor 2, accounted for 25% of the total variance, and it was significantly correlated to Al and Fe. On the contrary, Factor 1, explained 41% of the total variance in the year 2006, and it was significantly correlated to Al and Fe, while Factor 2 accounted for 31% of the total variance and it was significantly correlated to Pb, Cu, and Zn. 4. Discussion Rome represents an example of a mega city where air pollution has been increasing over time, causing risks to the health of the population. The urbanisation process in Rome has been increased during the last few years, and many new suburban areas have been built by scaling down free areas surrounding the city (129.000 ha of urbanised area, 2.810.931 inhabitants, with 32.569 in the historical centre). Moreover, a strong increasing of the private means of transportation (56% increase of the vehicular park in Rome from 1985 to 2006, data from ACI, 2006) has been monitored. Air pollution in Rome is most likely due to emissions from motor vehicles (Moreno et al., 2003). Consequently, in these last years the City Council has promulgated some provisions to limit pollution levels, such as the LTZ introduction in the historical centre of the city. The mean value of the total traffic flow, during the limited period, was 75.000 vehicles, compared to 90.000 ones before the electronic gates where activated; moreover, a 15% decrease in the daily traffic peak (8:30–9:30 a.m) was monitored (data from ATAC Mobilty Agency, 2006). Although metals are naturally present in soils, contamination comes from local sources, mostly industry, agriculture, sewage sludge, waste incineration, and road traffic (Çelik et al., 2005). Zn, Fe and Cu are microelements essential for plants (Shuman, 1994), and they are natural constituents of the soil (Larcher, 2003); nevertheless the source of Zn and Cu in the street dust has been ascribed to corrosion of the metallic parts of cars like engine wear, thrust bearing and brush wear (Divrikli et al., 2003; Al – Khashman and Shwabkeh, 2006). Pb is directly related to the emissions from motor vehicles (Koeppe, 1981; Al – Khlaifat and Khashman, 2007). On the whole, our results underline the effects of the Council provision throughout the use of Q. ilex leaves. The 8276 L. Gratani et al. / Atmospheric Environment 42 (2008) 8273–8277 metal concentration in Q. ilex leaves seems to be related to motor vehicle emissions; Çelik et al. (2005), Al – Alawi and Mandiwana (2007), and Urbat et al. (2004) underline the relationship between motor vehicle emissions and metal concentration in leaves of Robinia pseudo – acacia L. Pinus halepensis L., and Pinus nigra L., respectively. On an average, Q. ilex leaves accumulated more metals in 1979, when there were a greater number of motor vehicles in the historical centre than in 2006, according to the results of Kapusta et al. (2006) for Moehringia trinervia Clairv. The PCA underlines that in 1979, when LTZ had not been established yet, and there was a higher Pb concentration in gasoline, Factor 1 (describing most of the total variance) is dominated by Pb and Zn, which are directly correlated to motor vehicles (Al – Khlaifat and Khashman, 2007). In the years following 1979, a significant increase of the traffic density has been observed (1.582.754 vehicles registered in 1985 to 2.476.179, in 2006). Starting from 1990, further measures have been taken in Italy to limit pollution levels increasing; since 1989 ‘‘green’’ fuel and catalytic exhausts have become compulsory, and in 1989, the Rome City Council have introduced the traffic limitation zones (LTZ) in the centre of the city. The effects of these provisions resulted in a significant traffic density lowering, that is underlined by PCA; in fact, the Factor 1, explaining most of the total variance in the data monitored in 2006, is dominated by Fe and Al, which are typical soil constituents (Rossini Oliva and Mingorance, 2006); on the contrary, the concentration of Zn, Cu and Pb, which are directly related to the traffic density (Çelik et al., 2005; Al – Khlaifat and Khashman, 2007) are correlated to Factor 2, accounting for a lower variance. Total element contents in the aboveground parts of plants depend on the root uptake and elements re-translocation from the assimilation organs (Garland et al., 1981; Zimcka and Stackurski,1994). It has also been suggested that direct uptake through bark or foliage may be a major pathway by which metals enter trees, particularly in heavily polluted areas (Baes and McLaughlin, 1987). The wood accumulates elements mainly from the soil, and its metal concentration does not reflect the atmospheric pollution making this plant portion unsuitable for bio-monitoring (Rossini Oliva and Mingorance, 2006). It is possible to measure differences between aerial deposition and root uptake through washing leaves (Matarrese Palmieri et al., 2005). Plant bark and leaves accumulate pollutants straight from the atmosphere and they are deposited mainly on the surface (Rossini Oliva and Mingorance, 2006): our results underline that the mean metal concentration of Q. ilex leaf surface is 74% of the total concentration. The obtained data of the leaf metal concentration trend in Rome over a period of 27 years, and in relationship with the traffic density, underlines the importance of the City Council provisions. These results may be used to carry out a data-bank improving the City Council management. Understanding the relationship among urban trees, people, and the environment can facilitate future urban designs, that might enhance environmental and social benefits (Dwyer et al., 1992). According to Market (1993) and Al-Alawi and Mandlwana (2007), the basic criteria for the selection of a plant to bio-monitor are that it should be represented in large numbers all over the monitoring area, be easy and inexpensive to sample, and determine a 50% saving over the use of pollution monitors. Moreover, the main advantage is that plants are wide-spread, providing a high density of sampling points, so there is the possibility of building high-resolution maps of air pollution in urban areas (Moreno et al., 2003). Our results suggest the use of Q. ilex for long-term monitoring of metal concentration in those urban areas where the species is naturally present and widely distributed, according to the results of Alfani et al. (1996), Maisto et al. 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