Environ Sci Pollut Res DOI 10.1007/s11356-015-5890-8
BIOMONITORING OF ATMOSPHERIC POLLUTION: POSSIBILITIES AND FUTURE CHALLENGES
Heavy metal and polycyclic aromatic hydrocarbon concentrations in Quercus ilex L. leaves fit an a priori subdivision in site typologies based on human management Flavia De Nicola 1 & Daniela Baldantoni 2 & Giulia Maisto 3 & Anna Alfani 2
Received: 29 June 2015 / Accepted: 27 November 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract Concentrations of four heavy metals (HMs) (Cd, Cr, Fe, Pb) and four polycyclic aromatic hydrocarbons ( PA H s ) ( f l u o r a n t h e n e , p h e n a n t h r e n e , c h r y s e n e , benzo[a]pyrene) in Quercus ilex L. leaves collected at the Campania Region (Southern Italy) in previous air biomonitoring studies were employed to (1) test the correspondence with an a priori site subdivision (remote, periurban, and urban) and (2) evaluate long temporal trends of HM (approximately 20 years) and PAH (approximately 10 years) air contaminations. Overall, Q. ilex leaf HM and PAH concentrations resulted along the gradient: remote < periurban < urban sites, reflecting the a priori subdivision based on human management. Over a long time, although a clear decrease of leaf Pb, chrysene, fluoranthene, and phenanthrene concentrations occurred at the urban sites, a high contamination level persists.
Keywords Holm oak . Inorganic and organic pollutants . Long-term biomonitoring . Air contamination gradients . Campania Region (Southern Italy)
Responsible editor: Constantini Samara * Daniela Baldantoni
[email protected] 1
Dip. Scienze e Tecnologie, Università degli Studi del Sannio, via Port’Arsa 11, 82100 Benevento, Italy
2
Dip. Chimica e Biologia BAdolfo Zambelli^, Università degli Studi di Salerno, via Giovanni Paolo II 132, 84084 Fisciano, SA, Italy
3
Dip. Biologia, Università degli Studi di Napoli Federico II, via Cinthia, 80126 Naples, Italy
Introduction Recently, some heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs), widely recognized as carcinogenic and teratogenic pollutants (IARC 2013). have been considered as causes of many human diseases. Therefore, the BDirective on ambient air quality and cleaner air for Europe^ (Directive 2008/ 50/EC) states that air HM and PAH concentrations must be routinely monitored. These pollutants are emitted in the air by various mobile and stationary sources (motor vehicles, domestic heating, power plants) that are very abundant in urban or industrial areas, and may also move to remote areas. Anyway, air pollutant emissions in remote areas (biological activities, fires, or pedogenetic alterations) are not negligible. Inhalation and ingestion of contaminated food are among the main intake ways of these pollutants by humans (Ravindra et al. 2008a). Due to the high costs for installation and maintenance, the monitoring stations can be usually placed only at a few critical sites of the cities. Thus, the deriving data can represent a local situation and cannot be extended to wider areas. To bypass these inconveniences (i.e., costs and area representation), living organisms can be effectively used to monitor air quality. Besides, living organisms, accumulating air pollutants during their exposure time, can be also used to assess air quality either at a brief or long term (Alfani et al. 1996, 2000, 2005; De Nicola et al. 2005; Aničić et al. 2011). In the last decades, as biomonitoring experienced great interest, the Directive 2004/107/EC (arsenic, cadmium, mercury, nickel, and polycyclic aromatic hydrocarbons in ambient air) also recommends, in addition to mandatory measurements, the use of bioindicators to assess contamination patterns at a regional scale. In this frame, many higher plants can be effectively used as biomonitors of air quality as their morphology, physiology, and ecology are better known than in lower plants (Wittig 1993) and as leaf age and exposure time can be easily recognized (Bargagli
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et al. 1998). Leaves can accumulate air gaseous and particulate pollutants by stomata and/or by interception, impaction, or sedimentation on leaf surface, and leaf morphological characteristics (i.e., surface area, presence of tricomes, chemistry of cuticular waxes) play an important role in particulate pollutants adsorption (Wittig 1993; Song et al. 2015). Despite soil can contribute to leaf pollutant concentrations, some HMs are accumulated in the roots and scarcely translocated to the aboveground plant portion (Domínguez et al. 2011) whereas PAHs are negligibly absorbed by roots (Simonich and Hites 1995). The aim of this paper was to test the correspondence between an a priori subdivision of sites of Campania Region (Southern Italy) in three typologies (remote, periurban, and urban) on the basis of human management and the concentrations of HMs (Cd, Cr, Fe, and Pb) and PAHs (benzo[a]pyrene, chrysene, fluoranthene, and phenanthrene) in leaves of Quercus ilex L., a typical Mediterranean tree, widely employed as biomonitors (Alfani et al. 2000; De Nicola et al. 2005, 2011). In addition, this paper aimed to evaluate, through the leaf analyses, temporal trends of the inorganic and organic pollutants over a long period (approximately 20 years for HMs and 10 years for PAHs).
Materials and methods Background The data reported in this paper come from the analyses of Q. ilex leaves sampled and processed in previous studies,
Fig. 1 Remote (diamonds), periurban (triangles), and urban (circles) sites of Campania Region (Italy) where HMs (white), PAHs (gray), or both (black) were investigated (9 remote, 8 periurban, and 26 urban sites for HMs; 4 remote, 6 periurban, and 18 urban sites for PAHs)
according to standardized procedures. These studies were performed in order to respond to relevant and different subjects about biomonitoring and here synthetically reported: (1) the possibility to use Q. ilex leaves as biomonitors of air quality through the evaluation of HM and PAH concentrations; (2) the correspondence between leaf pollutant accumulation and leaf time exposure; (3) the leaf uptake of air pollutants and their accumulation in the tissues or on the surface of leaves; and (4) the relationships between leaf and soil concerning these two classes of pollutants. Considered the great number of observations (43 sites for HMs and 28 sites for PAHs) and the long data series (1989–2009 for HMs and 1998–2009 for PAHs), the authors propose to use all the previously obtained data to respond to the aims of this paper. Sampling sites and sample collection The employed sampling sites of the Campania Region (Southern Italy) were grouped, basing on the human management, into three site typologies: remote (9 sites for HMs and 4 for PAHs), periurban (8 and 6 sites for HMs and PAHs, respectively), and urban (26 sites for HMs and 18 for PAHs) (Fig. 1). The study area is characterized by a Mediterranean climate, with warm and dry summers and cold and rainy winters (a climate diagram of the area is reported in De Nicola et al. 2013). At each site, 4–8 Q. ilex trees were chosen to perform the leaf samplings. Small branches located 2–4 m above the ground and from the outer part of the canopies were cut by pruning shears. In order to
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Fig. 2 Non-metric multidimensional scaling (NMDS) biplot of HMs in Q. ilex leaves from remote (diamonds), periurban (triangles), and urban (circles) sites of Campania Region (Italy). The temporal gradient (gray lines) and the confidence ellipses (α=0.05) for remote (dotted), periurban (dashed), and urban (solid) sites are also shown
obtain a homogeneous sample, a large number of 1-year old leaves was collected by hand, taking into account that the leaf bud break mainly occurs each year in May (De Lillis and Fontanella 1992). The samplings were carried out minimizing the contact with the leaf surface. The unwashed leaves were differently treated to measure the HM and PAH concentrations. HM and PAH determinations For HM analyses, leaves were oven dried at 75 °C until constant weight and pulverized with agate ball mills, using a Fritsh Pulverisette or a Retsch PM4. Subsequently, the powder was used to prepare three replicates. The samples (250 mg) were mineralized with the addition of 4 ml 65 % HNO3 and 2 ml 50 % HF in a microwave oven system (Milestone, Ethos) and diluted to a final volume of 50 ml, as reported in Baldantoni et al. (2009). Sample mineralization was obtained through the following steps: 250 W for 2 min, 0 W for 2 min, 250 W for 5 min, 400 W for 5 min, 0 W for 2 min, and 500 W for 5 min. The metal concentrations were detected using Varian (AA20) and PerkinElmer (AAnalyst 100) atomic absorption spectrometers, via graphite furnace (Cd, Cr, and Pb) or flame (Fe). Multipoint linear calibration curves were performed for each HM; when outside the linear range, the samples were adequately diluted. In order to ascertain the accuracy of the employed method and the right quantification of the
investigated HMs, a concurrent analysis of reference materials was carried out (Olive leaves BCR62 and Pine needles NIST1575a), obtaining percentage recoveries of 80–86 % for Pb, 94–98 % for Cr, 98–100 % for Fe, and 105–110 % for Cd. The precision of the method, calculated as relative standard deviation (n=9), was 2 % for Pb, 5 % for Cr and Fe, and 9 % for Cd. For PAH analyses, fresh leaves (5 g) were extracted by three consecutive sonications (Misonix, XL2020 sonicator), each in 100 ml of a mixture of dichloromethane and acetone (1:1 = v/v). Subsequently, the extracts were reduced in volume (De Nicola et al. 2005) and the concentrations of fluoranthene (Flt), phenanthrene (Phen), chrysene (Crys), and benzo[a]pyrene (B[a]P) were detected by gas chromatography coupled to mass spectrometry detector (HP 5890/5971). The GC-MS conditions were described in De Nicola et al. (2005). To quantify the PAHs, multipoint calibration curves were performed using standard mixtures. To evaluate the extraction efficiency, labeled PAHs (phenanthrene-d 10 , chrysene-d 12 , and perylene-d 12) at known concentrations, were added to each sample before the extraction. The percent recovery of labeled PAHs, approximately of 70 % for each, was used to correct the quantification of the investigated PAHs. The precision of the method, calculated as relative standard deviation (n=6), ranged from 4 % for Phen to 12 % for B[a]P. For each leaf sample, the PAH analyses were carried out in triplicates. Data analysis The overall differences in leaf HM and PAH concentrations among site typologies and among sampling times were evaluated using two-way multivariate analysis of variance (MANOVA) and non-metric multidimensional scaling (NMDS). The MANOVA models, with the HMs or the PAHs as dependent variables and the site typologies and sampling times as fixed factors, were based on the Pillai’s statistic. Upon the NMDS HM and PAH ordinations, based on the Euclidean distance and on two axes, the confidence ellipses (for α = 0.05) for the three site typologies, as well as the temporal fields evaluated through cubic splines, w ere superimposed. The MANOVAs were followed by ANOVA models for each dependent variable, using the site typologies and sampling time as fixed factors. The Tukey HSD post hoc test was then employed to evaluate differences among each pair of site typologies. Homoscedasticity and normality of the residuals were assessed using the Breuch-Pagan and the Kolmogorov-Smirnov tests, respectively. All the analyses were performed using the R 3.1.1 programming environment (R Core Team 2014) with functions from the Bstats^, Bvegan^, Bmgcv^, Bnortest^, and Blmtest^ packages.
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Cd ( g/g d.w.)
Fig. 3 HM concentrations (mean values±standard errors of the means) measured in Q. ilex leaves collected from 1989 to 2009 in remote, periurban, and urban sites of Campania Region (Italy)
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Results Heavy metals Leaf metal concentrations widely varied among the sites, and the ranges were 0.001–0.693 μg g−1 dry weight (d.w.) for Cd,
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0.03–10.03 μg g−1 d.w. for Cr, 0.1–4.5 mg g-1 d.w. for Fe, and 0.01–147.86 μg g−1 d.w. for Pb. The MANOVA test, considering the leaf concentrations of all HMs, highlighted significant differences among the site typologies (P
