Int. J. Environment and Health, Vol. 4, Nos. 2/3, 2010
Leaves of Lolium multiflorum as indicators of airborne trace element distribution in Central Italy Alessandra Francini, Cristina Nali* and Giacomo Lorenzini Department of Tree Science, Entomology and Plant Pathology ‘G. Scaramuzzi’, University of Pisa, Pisa, Italy Email:
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[email protected] *Corresponding author
Stefano Loppi Department of Environmental Sciences ‘G. Sarfatti’, University of Siena, Siena, Italy Email:
[email protected] Abstract: Ambient air contains particles, ranging from sub-micrometric aerosols to clearly visible dust and sand grains. Plants during evolution developed the ability to maximise light interception and CO2 assimilation and also the efficiency to collect the airborne pollutants. Therefore, plant tissues have been used as indicators of trace elements air pollution. Lolium multiflorum leaves were used as a sampler to describe the distribution of selected elements in the area of Carrara (Tuscany, Central Italy). Unwashed healthy leaves collected in September 2007 from nine sampling sites were analysed by ICP-MS. Enrichment factors (EFs) were calculated taking Al as crustal reference element. Cd and Mo exhibited the highest EFs, with some values above 10,000. Varimax rotated factor analysis identified three main source groups of elements, namely crustal components, marine aerosol spray and anthropogenic sources. Keywords: air pollution; air quality; biomonitoring; enrichment factor; factor analysis; heavy metals; ICP-MS; inductively coupled plasma-mass spectrometry; pollution sources; source apportionment. Reference to this paper should be made as follows: Francini, A., Nali, C., Lorenzini, G. and Loppi, S. (2010) ‘Leaves of Lolium multiflorum as indicators of airborne trace element distribution in Central Italy’, Int. J. Environment and Health, Vol. 4, Nos. 2/3, pp.151–165. Biographical notes: Alessandra Francini received her PhD in Advanced Technology in Horticultural Science at the University of Pisa (Italy). She has a background in abiotic stresses in soil-plant systems, with special concern about
Copyright © 2010 Inderscience Enterprises Ltd.
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A. Francini et al. heavy metals and gaseous air pollutants. She is also engaged in studies on plant secondary metabolites involved in plant defence responses, with particular reference to those induced by abiotic stresses, such as ozone. Cristina Nali is Assistant Professor at the Faculty of Agricultural Sciences in the University of Pisa (Italy). She has a background in plant pathology, with special concern about the interactions between fungal diseases and gaseous air pollutants. Her research interests are interactions between air pollutants and plants, especially biological monitoring and the study of physiological and molecular bases for differential response of plants to the oxidative stress. Giacomo Lorenzini is Professor of Plant Pathology at the Faculty of Agricultural Sciences in the University of Pisa (Italy). He has a background in plant pathology, with special concern on crop protection and phytotoxicity of air pollutants. His research interests also cover biological monitoring of air pollutants and ecophysiological aspects of air pollutant toxicity. Stefano Loppi is Assistant Professor at the Department of Environmental Sciences ‘G. Sarfatti’ of the University of Siena (Italy). His research activity is addressed to environmental biomonitoring, with emphasis on the use of lichens as bioindicators of air pollution. He is a member of the editorial board of the journal Environmental Pollution and author of more than 150 scientific publications.
1
Introduction
Trace elements are widely dispersed in the environment and their interactions with different natural components result in a wide range of human disorders and ecological damages (Aničić et al., 2009). Biogeochemical cycles of elements may be very complex. Chemical substances may be released into the atmosphere during the combustion of fossil fuels and their derivatives (such as gasoline and diesel fuel), as well as from several industrial processes and waste incinerators. Natural emissions result from a variety of processes acting on crustal materials, including wind erosion, as well as from forest fires and the oceans. Airborne trace elements are mainly bound to particles. Elemental carbon and inorganic anions, such as nitrate and sulphate, are generally the main constituents of PM10 (Putaud et al., 2004), but trace metals may also play a major role concerning toxicity and ecotoxicity of dust particles and their adverse health effects (Valavanidis et al., 2006). This very important role can be explained by the observation that metals have a high affinity to the very fine and ultrafine aerosol fractions, as reported by Moreno et al. (2006). Such contaminants, transported through air mass movements, are deposited by dry and wet deposition and intercepted by plant canopies: the leaves accumulate airborne particulates by interception, impaction or sedimentation. Therefore, they may be taken up directly via the stomata or simply deposited on the leaf surface (De Nicola et al., 2008). Continuous measurement by chemico-physical methods using stationary or mobile automatic gauges is the major source of information on atmospheric pollution. These measurements are essential to define the ambient concentrations of pollutants, but, conversely, are of minimal use to evaluate their biological impact. In addition, many
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elements are present in the atmosphere at very low concentrations, and as a consequence they are rarely considered in standard monitoring networks (Bargagli, 1998). Particularly, the use of plants for environmental diagnosis should be regarded as a necessary complementary tool to be integrated with classical instrumental monitoring. Plants have evolved to maximise light interception and carbon dioxide assimilation and as a consequence they are also highly efficient receptors of airborne pollutants; the use of plant tissues has since long been shown to be an effective indicator of metal air pollution (Goodman and Roberts, 1971). Moreover, vegetation is an effective indicator of the overall impact of air pollution, and the effect observed is a time-averaged result, which is more reliable than the one obtained from direct determination of the pollutant in air over a short period. In many cities, studies of metal accumulation by higher plants, lichens and mosses have been carried out (for further details, see Rossini Oliva and Valdés, 2004). Biomonitoring of trace element pollution is usually conducted by using passive or active bioindicators, since atmospheric levels of heavy metals and other trace elements generally do not cause visible injury. Passive biomonitoring is the use of organisms which are a natural component of the ecosystem. Active biomonitoring includes all methods which insert organisms under controlled conditions into the site to be monitored. For biomonitoring of trace elements, both the strategies are well documented (Fernández Espinosa and Rossini Oliva, 2006; Lorenzini et al., 2006; Nali et al., 2009). On the other hand, it is well known that plants accumulate trace elements offering low-cost information about environmental quality with the high advantage of the easy sampling. However, uptake of metal pollutants in plants depends on many factors, but climatic conditions are very important and play a fundamental role. In addition, leaf surface properties, as well as morphology, chemistry of the waxy components and different shapes and sizes affect retention capability (Monteith and Unsworth, 1990). Furthermore, pubescent leaves have been shown to have greater scavenging efficiency than hairless ones (Little and Wiffen, 1977) and, more, roughness and integrity of the cuticle affect adhesion on the leaf surface (Neinhuis and Barthlott, 1997). In the present report, Lolium multiflorum (Italian ryegrass) was chosen as a bioindicator species because the spatial distribution of leaves in the canopy is dense and this allows a good impact on surface. This species presents a high capacity for the accumulation of toxic substances, as well as a high tolerance against most air pollutants, without showing any visible injury due to ambient pollution levels. Being a commonly grown fodder plant, the accumulation of toxic substances in ryegrass may serve for estimating the potential biomagnification of contaminants along the food chain and the potential health risk for humans and livestock (Klumpp et al., 2009). That makes this plant particularly suitable for measuring atmospheric levels of trace elements. Results of an active biomonitoring survey (Steubing and Jaeger, 1982) of air quality carried out in the area of Carrara (Tuscany, Central Italy) – a city very famous for the marble extracted from nearby Apuane Alps – are reported. Anthropogenic activities, that produce atmospheric pollution (i.e. the contribution of heavy vehicular traffic, that daily transports marble), were investigated by factor analysis (FA), that was employed to detect likely sources of critical elements detected on/in plants ad hoc grown in standardised conditions in several locations.
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Materials and methods
2.1 Study area The Tuscan municipalities of Carrara (100 m a.s.l.) were selected for this study. Carrara has a population of ca. 65,000 inhabitants and a surface of about 71 km2, thus showing a population density of about 900 inhabitants km–2. The climate of the area is subMediterranean, characterised by temperatures varying from 3 (January) to 29°C (July and August), with an average of 15°C and a mean annual rainfall in a range of 1000 mm. A sea-to-land and vice versa breeze system is the dominant anemological regime, but significant winds come from the second (SSE) and third (SSW) quadrants. The local economy is mainly based on the mining and processing of the valuable worldwide famous marble of Carrara. The city was divided into regular sectors (squares of 1.2 × 1.2 km) and in each sector a sampling point was randomly selected according to a systematic stratified unallineated sampling design for a total of nine stations (Table 1). Table 1
Location of monitoring stations of Lolium multiflorum exposed from 6 August to 4 September 2007 at Carrara
N.
Location
Longitude, N
Latitude, E
1
Via Giovan Pietro
44°02'56.90"
10°03'33.92"
2
Viale Galilei
44°03'11.63"
10°02'26.09"
3
Viale Giovanni da Verrazzano
44°01'50.37"
10°03'27.09"
4
Via Cà Marchetti
44°03'18.66"
10°01'53.40"
5
Via Agricola
44°04'33.15"
10°04'27.45"
6
Via di Santa Lucia
44°04'23.53"
10°03'46.42"
7
Corso Carlo Rosselli
44°04'29.82"
10°05'44.30"
8
Via Colonnata
44°04'56.16"
10°06'19.45"
9
Via Frassina
44°02'38.37"
10°05'11.04"
2.2 Cultivation and field exposure of grass cultures Seeds of Italian ryegrass L. multiflorum Lam. cv. Lema were grown directly into plastic trays (10 × 30 × 40 cm). Two glass fibre wicks (Ø 5 mm) were inserted through holes in the bottom of each tray to provide water supply. The trays were filled with commercially available, non-fertilised standardised substrate (Type 0; Patzer Einheitserde) up to 6 cm from the edge; the substrate was then compacted, the seeds sown on the surface (5 g of seed were used to obtain the same number of plants in each plateau) and another layer of substrate (1 cm) added. The soil surface was moistened by spraying with deionised water, and pots were placed upon water-filled basins, so that the wicks were hanging into the water, thus supplying the grass cultures with water. Drying during the germination phase was avoided by occasional spraying with water. The cultures were regularly fertilised with an NPK solution made from analytic-grade chemicals. When the blades reached a height of 8–10 cm, the cultures were cut back to a stubble height of 4 cm to stimulate tillering. Further cut-backs were made every 8–10 days during cultivation and finally one day before the start of field exposure.
Leaves of Lolium multiform as indicators
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After greenhouse cultivation for six weeks, the grass cultures were exposed to ambient air at the selected stations. Two grass cultures were used for each exposure site. The experiment was performed from 6 August to 4 September 2007. No pesticide or fertiliser was applied. After the exposure to ambient air, the cultures were harvested and the plant material grown during the exposure period was cut at 4 cm height. Samples with less than 2 g dry weight (d.w.) were rejected to avoid artefacts due to irregular growing conditions during exposure periods. Dead or yellow leaves, as well as leaves showing visible signs of parasites, were discharged. Samples were oven dried at 75°C until constant weight and then crushed to a fine powder and homogenised with a mill.
2.3 Elemental analysis Total concentrations of Al, As, Ba, Be, Bi, Br, Ca, Cd, Cl, Co, Cr, Cs, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Sb, Si, Ti, V and Zn in the unwashed leaf samples were determined. About 100 mg of powder were mineralised with a 6:1 (v:v) mixture of ultrapure concentrated HNO3 and H2O2 at 280°C and a pressure of 0.55 MPa in a microwave digestion system (Milestone Ethos 900). Element concentrations, expressed on a DW basis, were determined by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS, Perkin Elmer-Sciex Elan 6100). Analytical quality was checked with the Certified Reference Material CRM-062 ‘olive leaves’. Accuracy was within 7% for all elements. All analyses were carried out in triplicate.
2.4 Statistics Data were evaluated by one method reported in Klumpp et al. (2009), which permits one to calculate process-inherent background (BV) and threshold values (i.e. Effect Detection Limits, EDL). In this procedure, the numerous low values in the study area, which indicate only a low pollution impact, are used as reference values. First, mean values and standard deviation were calculated for the group of sites. Subsequently, single values exceeding a filter threshold (Fj), defined as mean value (xj) plus 1.96 times the standard deviation (sd) (Fj = xj + 1.96 sd), were removed from the data collective and the new mean value is calculated. This procedure was repeated until no values exceeded the filter threshold. The remaining values were used as reference values, and the arithmetic mean of the reference values was defined as local background value (BVlocal). EDL was defined as mean background value plus the threefold standard error (Erhardt et al., 1996). For graphic presentation of data, box-whisker plots were drawn for each element. Following performance of the Shapiro–Wilk (W) test, differences among stations were evaluated by ANOVA and subsequent LSD test. Relationships between the contents of individual elements were tested using correlation analysis and determination coefficient (R2) was computed. To have an indication of the relative contribution of crustal contamination to the bulk of element distribution in/on the leaves, the enrichment factor (EF) has been calculated for each element assayed, taking Al as reference element (Al is an element of limited metabolic significance in plants and is widely distributed in the earth’s crust; furthermore, we have assumed that in the study area anthropogenic sources of Al to the atmosphere
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are negligible). The average crustal composition reported by Taylor and McLennan (1985) was also adopted. The dimensionless EF for any element X relative to crustal material is defined by EF = ( X Al )leaf
(X
Al )crust
where (X/Al)leaf is the concentration ratio of X to Al in the plant sample, and (X/Al)crust is the average concentration ratio of X to Al in the crust. By convention, the average elemental concentration in the crust is used, mostly because particles may be subjected to long-range transport phenomena and the characterisation of specific areas is not easy (Chester et al., 2000). As a rule of thumb, if EF approaches unity, crustal is the predominant source; EFs up to 10 may be considered not to be significantly enriched, due to differences in the chemical composition of local soil and the reference crustal composition; elements with EFs between 10 and 100 should be considered as enriched and those with EF greater than 100 as highly enriched, indicating a heavy contribution of non-crustal sources (Duce et al., 1975). Elemental compositions of whole unwashed leaves, as resulted from ICP-MS analysis were subjected to varimax rotated factor analysis, a multivariate statistical treatment frequently used in atmospheric pollution research to obtain information on pollution sources (e.g. Hopke et al., 1976; Plaisance et al., 1997). FA separates a given set of elements into groups or factors based on their fluctuation and common variance, provided that each association of chemical species found in the FA is related to an identifiable source type known in advance. The varimax rotation improves the orthogonality of the resolved factors. Factors with eigenvalues greater than 1 (before rotation) have been considered to be significant (Kaiser, 1960). The communalities, which represent the amount of variance of each element explained by the factorial model, are also shown. With cluster analysis using squared Euclidean distance as a measurement of distance and the Ward algorithm as an agglomeration procedure, the monitoring points were sub-classified into groups (clusters) according to their relative similarity.
3
Results and discussion
Table 2 gives the mean values, BVlocal and EDL. Five stations (#3, 4, 6, 8 and 9) were characterised by lower mean values than BVlocal for the majority of the elements analysed. Higher metal levels were detected in three stations (#1, 5 and 7). The first station presented the highest levels for 9 out of 27 elements analysed. EDL was totally exceeded 14 times: Sb was over three times; Mg and Na twice. Sb in Station # 7 was 4.5 times higher than EDL. Only 10 elements (Al, Bi, Cd, Cu, Mg, Mo, Na, Ni, Pb and Sb) were over EDL at least once. Figure 1 shows a detailed overview of the concentrations of individual trace elements and their variability among biomonitoring sites. Large scattering of concentrations was observed for Al, Br, Cd, Ni and Sb. For another groups of elements comprising Ba, Bi, Cs, Cu, Mg, Mo, Pb, Si and Zn, no scattering of values was found. This is indicative of no clear location-specific differentiation regarding traffic intensity or other potential emission sources.
Leaves of Lolium multiform as indicators Table 2
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Minimum and maximum and local background (BVlocal) values and the Effect Detection Levels (EDL) of trace element concentrations in/on leaves of Lolium multiflorum exposed from 6 August to 4 September 2007 in the nine stations of Carrara
Station
Range
BVlocal
EDL
Al
18–114
51
110
As
0.4–0.8
0.6
1.1
Ba
15–26
19
28
Be
0.008–0.065
0.030
0.091
Bi
0.01–0.05
0.01
0.02
Br
181–565
297
642
Ca
5501–7952
6460
8711
Cd
0.15–1.44
0.30
1.07
Cl
1561–6698
4248
11285
Co
0.4–0.7
0.5
0.7
Cr
1.9–3.2
2.5
3.9
Cs
0.17–0.23
0.20
0.29
Cu
7–20
9
14
Fe
87–245
173
334
K
15556–31036
23132
38030
Li
1.2–3.2
2.4
5.6
Mg
3055–4162
3407
4062
Mn
129–323
224
419
Mo
10–19
13
18
Na
1522–4545
2195
3933
Ni
1.3–5.6
2.3
4.6
Pb
0.7–1.6
0.9
1.5
Sb
0.02–0.59
0.05
0.13
Si
71–122
91
135
Ti
11–28
20
41
V
1.3–2.3
1.7
3.3
Zn
36–67
47
79
Notes:
All values are given in mg kg–1 DW. Calculation followed the procedure described by Klumpp et al. (2009).
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Figure 1
Box-and-whiskers representation of the content of selected trace elements in unwashed samples of Lolium multiflorum exposed from 6 August to 4 September, 2007 in the nine stations of Carrara. For each element, the top line represents the 90th percentile, the bottom line represents the 10th percentile and the box represents the 75th percentile (upper side), the 25th percentile (lower side) and the median (50th percentile, central line), respectively
Concentration (mg kg-1)
0.3
1.8
0.2
1.2 0.1
0.0 Concentration (mg kg-1)
10
0.6
Be
Bi
0.0
Cs
80
8
As
Cd
Pb
Co
Sb
Ba
Cu
Mo
Ti
Zn
Ca
Cl
K
Mg
Na
60
6 40 4 20
2 0
Concentration (mg kg-1)
2.4
Li
Ni
V
Cr
0
30000 25000 20000
600
400
9000 6000
200
3000 0
Al
Br
Fe
Mn
Si
0
Data of our reference plants showed a good fitting with the ranges of occurrence in higher plants proposed by Markert (1992), with the only notable exceptions of As, Br, Cd, Cl, Na and Mo, whose levels are significantly higher in our plants. For As, our data, however, are well in line with those reported by Klumpp et al. (2009). High levels of Na, Cl and Br can be related to marine contribution: Br is a minor but peculiar component of sea water, with concentrations of the order of 100 mg dm–3, and is injected into the atmosphere with sea-salt aerosol by breaking waves, this pathway being the principal global source for atmospheric Br, especially in the sub-micrometric fraction (Sander et al., 2003). Wind transported sea-salts are a common feature for coastal areas of Tuscany, but
Leaves of Lolium multiform as indicators
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significant amounts of this element are also found in areas such as Florence city (Lucarelli et al., 2000), which is more than 80 km away from the coastline. Cd and Mo values are similar to those observed by Lorenzini et al. (2006) and Rossini Oliva and Valdés (2004). However, it necessary to note that background levels, proposed by Markert (1992, 1996) and also other authors, are indicative as factors such as litological characteristics, plant species and tissues may affect them (Nimis et al., 1993). Our data have been compared with those found in other networks using L. multiflorum as biomonitor. Generally, our observations are in agreement with the range of concentrations found by Klumpp et al. (2009). Data of Cd accumulation by ryegrass, on the contrary, showed value ten times higher that those found in 11 cities of European biomonitoring programme during 2000–2002 (Klumpp et al., 2009). Cd concentration found in our experiment was much more in accordance with data reported by Nobel et al. (2004), who found in the ryegrass during exposure experiments the average Cd levels of 0.6 mg kg–1 DW (dry weight). Our Cd concentrations were anywhere in the range of the applicable European thresholds for animal feed and foodstuffs, which are at 0.5–1.0 mg kg–1 DW for different feed materials (EU, 2005) and 0.1–0.2 mg kg–1 FW (fresh weight) for stem and leaf vegetables (EU, 2006). Correlation analysis revealed significant correlations between metals (Table 3). The typical crustal element Al showed good correlation with Ba, Br, Cr, Mn and Mo. Al was closely correlated with Cr and Mo and Cr with Fe and Mo, as also reported by Lorenzini et al. (2006) in leaves of Pittosporum tobira after exposure to ambient air in other locations of Central Italy. The Cl and V correlation was observed in lettuce leaves exposed to ambient air near Florence (Nali et al., 2009). Content of Pb was closely correlated with Sb, which arises primarily from the abrasion of vehicle brake linings, and Fe. As such, motor vehicle traffic may therefore represent the main emission for these pollutants (Klumpp et al., 2009). Closed associations were also reported for some major plant nutrients (Ca with Mg and Mn, Cu with K). In order to have an indication of the relative contribution of crustal contamination to the bulk of element distribution in/on the leaves, EF has been calculated for each element, taking Al as reference element (Figure 2). Cd and Mo exhibit the highest EFs: all of sampling sites have values over 1000. The dominance of non-crustal sources for these elements is irrefutable. EFs over 100 are shown by As, Ca, Cu, K, Li, Mg, Na, Ni, Sb and Zn. On the other hand, Si always showed values close to 1, indicating a clear crustal origin for this element. Very low EFs were observed for elements such as Bi, Fe and Ti, suggesting negligible contributions of non-crustal sources. EFs for Ba and V exceed 10 and only rarely 100. EF for Pb was
