Ryegrass cv. Lema and guava cv. Paluma biomonitoring suitability for estimating nutritional contamination risks under seasonal climate in Southeastern Brazil

Ecotoxicology and Environmental Safety 118 (2015) 149–157

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Ryegrass cv. Lema and guava cv. Paluma biomonitoring suitability for estimating nutritional contamination risks under seasonal climate in Southeastern Brazil Patricia Bulbovas n, Carla Z.S. Camargo, Marisa Domingos Instituto de Botânica, Caixa Postal 68041, São Paulo 04045-972, SP, Brazil

art ic l e i nf o

a b s t r a c t

Article history: Received 8 January 2015 Received in revised form 17 April 2015 Accepted 20 April 2015 Available online 4 May 2015

The risks posed by nutrient deposition due to air pollution on ecosystems and their respective services to human beings can be appropriately estimated by bioindicator plants when they are well acclimated to the study region environmental conditions. This assumption encouraged us to comparatively evaluate the accumulation potential of ryegrass cv. Lema and guava cv. Paluma macro and micronutrients. We also indicated the most appropriate species for biomonitoring nutrient contamination risks in tropical areas of Southeastern Brazil, which are characterized by marked dry and wet seasons and complex mixtures of air pollutants from different sources (industries, vehicle traffic and agriculture). The study was conducted in 14 sites with different neighboring land uses, within the Metropolitan Region of Campinas, centraleastern region of São Paulo State. The exposure experiments with ryegrass and guava were consecutively repeated 40 (28 days each) and 12 (84 days each) times, respectively, from Oct/2010 to Sept/2013. Macro and micronutrients were analyzed and background concentrations and enrichment ratios (ER) were estimated to classify the contamination risk within the study region. Significantly higher ER suggested that ryegrass were the most appropriate accumulator species for N, S, Mg, Fe, Mn, Cu and Zn deposition and guava for K, Ca, P and B deposition. Based on these biomonitoring adjustments, we concluded that the nutrient deposition was spatially homogeneous in the study area, but clear seasonality in the contamination risk by nutritional inputs was evidenced. Significantly higher contamination risk by S, Fe, K and B occurred during the dry season and enhanced contamination risk by Mn, Cu and Zn were highlighted during the wet season. Distinctly high contamination risk was estimated for S, Fe and Mn in several exposure experiments. & 2015 Elsevier Inc. All rights reserved.

Keywords: Air pollution Nutrient enrichment Lolium multiflorum Psidium guajava Biomonitoring Contamination risk

1. Introduction The industrial production, fuel combustion by light and heavy vehicles, energy production and fertilizer and herbicide applications in agriculture in major urbanized centers (such as metropolitan regions) are currently among the most important sources of anthropogenic nutrient deposition (Lehndorff and Schwark, 2010; Sawidis et al., 2011; Boian and Andrade, 2012). Several pollutants may deposit on natural and agricultural ecosystems and occur at toxic levels in their different compartments, even if they are essential macro and micronutrients (e.g. nitrogen, sulfur, iron, copper, zinc) (Lehndorff and Schwark, 2010). In such condition, reduced biomass production and disturbances in plant physiology and biochemistry may be expected due to both direct and indirect effects induced by nutritional imbalances and n

Corresponding author. Fax: þ 55 11 50733678. E-mail address: [email protected] (P. Bulbovas).

http://dx.doi.org/10.1016/j.ecoenv.2015.04.024 0147-6513/& 2015 Elsevier Inc. All rights reserved.

acidification. Disproportional ratios between nitrogen and phosphorus or mobile cations, for instance, are commonly reported in native plant species growing in forest ecosystems affected by anthropogenic N deposition (van den Berg and Ashmore, 2008; Huang et al., 2012). The risks posed by anthropogenic nutrient deposition on natural or agricultural ecosystems due to air pollution can be estimated by bioindicator plants, which are able to react in a predictable and quantifiable way to environmental disturbances by changing their chemical composition or vital functions (Arndt and Schweizer, 1991; Fräinzle, 2003; Markert et al., 2003; Abril et al., 2014). However, we may assume that the validity of risk prediction using bioindicator plant species will depend on their acclimation level to the regional natural conditions. Ryegrass (Lolium multiflorum Lam. ssp. italicum Beck cv. Lema) has been well acclimated and appropriately used as a bioaccumulator of trace metals, sulfur, fluorine, and organic pollutants since the early 1970s in temperate regions. It has shown high tolerance against most air pollutants, without showing any visible

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injury due to environmental pollution levels (VDI, 2003; Klumpp et al., 2009). Some studies using ryegrass cv. Lema also highlighted its usefulness as a bioaccumulator in tropical regions (Klumpp and Klumpp, 1994; Klumpp et al., 1996; Domingos et al., 1998; Sandrin et al., 2008; Rinaldi et al., 2012; Nakazato et al., 2015). Wild guava (Psidium guajava) also seemed to be efficient as an accumulator plant of nitrogen, sulfur, fluorine and some few heavy metals, mostly micronutrients, in a tropical environment (Moraes et al., 2002). In addition, some studies revealed that guava cv. Paluma is also interesting for biomonitoring toxic elements in tropical regions (Perry et al., 2010; Nakazato, 2014). However, the satisfactory biomonitor properties of both species in tropical regions were only detected in areas with high water availability and affected by high levels of industrial air pollution, fact that raised the following question: which of them is more appropriate for biomonitoring anthropogenic nutrient deposition in tropical areas characterized by marked dry and wet seasons and generally by complex mixtures of air pollutants emitted by different sources, such as those found in the Metropolitan Region of Campinas (Southeast, Brazil)? In order to answer this question, the present study aimed at (1) comparing the accumulation potential of macro and micronutrients shown by ryegrass cv. Lema and guava cv. Paluma, indicating the most appropriate species for biomonitoring risks to natural and agricultural ecosystems associated with nutrient deposition in an area typically affected by alternate dry and wet seasons. (2) Verifying whether the risk posed by nutrient deposition varies among sites and seasons in the study region based on leaf accumulation in both cultivars.

2. Material and methods

Fig. 1. Total monthly rainfall and monthly averages of global radiation, relative humidity, temperature, particulate material, nitrogen dioxide and sulfur dioxide in MRC from October/2010 to September/2013.

2.1. Study area 2.2. Plant cultivation and field exposure The Metropolitan Region of Campinas (MRC), which is composed of 20 municipalities and located in the central-eastern region of São Paulo State, Brazil (Map, Supplementary material), was selected to be subjected to the field experiments because (a) It is the second most important economical center of São Paulo State, which is characterized by different land uses, among cities, highways, industries and extensive agricultural lands mainly devoted to sugarcane, orange and ornamental plantations (CETESB, 2013); (b) These activities emit considerable amounts of air pollutants (Tresmondi and Tomaz, 2004), which may potentially cause nutritional imbalances in crops and native plants growing in the Atlantic Semideciduous Forest remnants that still exist in MRC; (c) In addition to local emissions, the MRC is also affected by sizable emissions from the Metropolitan Region of São Paulo (MRSP), as a result of the predominantly southerly and southwesterly winds (Boian and Andrade, 2012); (d) Finally, more than three million people live close to these air, water and soil pollution sources in MRC, with consequent loss of ecosystem service quality. The biomonitoring using Lolium multiflorum Lam. ssp. italicum Beck cv. Lema (ryegrass) and Psidium guajava cv. Paluma (guava) was performed in fourteen sites within the MRC, which were categorized according to their major neighboring land uses: I1, I2 and I3 were located near an industrial pole; I/A was placed near the industrial pole and agricultural crops; A1, A2, A3, A4, A5, A6 and A7 were predominantly surrounded by agricultural crops, mainly sugarcane plantation; A/U was located near agricultural crops and an urban area; and U1 and U2 were close to urban areas (Map, supplementary material). The last one was chosen due to its proximity to an automatic air quality and weather conditions monitoring station. The sites A1, A4, A5, A6, A7 and A/U were close to the last Atlantic Semideciduous Forest remnants, a subtype of the Atlantic forest domain in Southeastern Brazil.

The following procedures were repeatedly performed to produce similar lots of plants in all field experiments. Ryegrass cv. Lema seeds (0.8 g per pot) were germinated and cultivated in plastic pots (1 L) containing a mixture of standardized substrate (Tropstrato Hortaliça HT) and vermiculite (3:1 v/v). During cultivation, the plants (approximately 20 grown in each pot) were weekly excised to a height of 4 cm above the substrate and fertilized with macronutrient solution recommended by Epstein (1975) (40 cm3 per pot), according to the protocol established by VDI (2003). Guava cv. Paluma saplings, with approximately 30 cm height and 12 leaves produced from the rooting of semi-herbaceous cuttings were taken from a specialized Brazilian producer. Fifteen days before the beginning of each field experiment, the saplings were transplanted into plastic pots (3.0 L) with the same standardized substrate used for the ryegrass (one sapling per pot). They were fertilized with 100 ml of a solution containing NPK (20:20:20) and insects and mites were controlled with tiametoxan 25% (Syngenta) applications. The plants of both species were kept inside a greenhouse under charcoal-filtered air and ideal climatic growth conditions throughout the cultivation process. They were continuously watered by nylon strings inserted into the bottom of the pots at one end and immersed in water reservoirs at the other. After growth, three pots of ryegrass cv. Lema plants were exposed in each of the fourteen sites for 28 days, following the methods suggested by VDI (2003). Ten potted saplings of guava cv. Paluma were exposed in the same sites on racks 1 m high from the soil surface for 84 days, following well-succeeded methods described by Moraes et al. (2002). These exposure experiments with ryegrass cv. Lema cultures and guava cv. Paluma plants were consecutively repeated 35 and 12 times, respectively, during the

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same experimental period (from October/2010 to September/ 2013), thus minimizing eventual biases due to unequal exposure times. At the end of each exposure experiment, the expanded leaves from each plant were collected. The leaf samples were oven-dried at 60 °C, milled in an agate mill and stored in polypropylene vials in order to determine macro and micronutrients. 2.3. Chemical analyses The N concentration was determined in aliquots of dried and milled leaf samples, after digestion with a solution mixture containing 30% hydrogen peroxide, lithium sulfate, selenium powder and sulfuric acid in a digester block that was gradually heated up to 350 °C. The nitrogen concentration was then measured by the Kjeldajhl method (Sarruge and Haag, 1974). Other aliquots of dried and milled leaf samples were digested in nitric acid at room temperature for 12 h and then gradually heated up to 160 °C. After partial evaporation, perchloric acid was added and samples were heated up to 210 °C. The resulting extract was diluted with deionized water and the K, Ca, Mg, B, Cu, Fe, Mn and Zn concentrations were determined by atomic absorption spectrophotometry. P and S were also determined in the same extracts by colorimetric and turbidimetric methods, respectively (Malavolta et al., 1997). The accuracy and precision of the analyses were checked by establishing concentrations of the same elements in analytical and methodological blanks and standard reference material. 2.4. Monitoring abiotic conditions Data regarding global radiation, relative humidity and temperature as well as concentrations of PM10, NO2 and SO2, which characterize the nutrient inputs in the MRC, were obtained from an automatic monitoring station located at the U2 site (available in www.cetesb.sp.gov.br/ar/). Rainfall data and global radiation were supplied by a meteorological station located next to I2 site, in the city of Paulínia. 2.5. Data evaluation and statistics First, background values (bv) of each nutrient analyzed in leaf samples of both species were estimated, following the method described by VDI (2003) and employed by Klumpp et al. (2009). The mean concentration (x1) of each element and respective standard deviation (s1) were calculated for the original dataset obtained in all exposure experiments for each species. After that, single values exceeding a threshold (tv) defined as the mean value plus 1.96 times the standard deviation (tv ¼x1 þ1.96 * s1) were removed from the mentioned dataset and a new mean value and standard deviation were then calculated. This procedure was repeated until no single concentration exceeded the threshold value. The arithmetic mean plus standard deviation of the final adjusted dataset was considered the background value (bv). After that, an enrichment ratio (ER) was calculated by dividing the single concentration of each element that composed the original dataset by the respective bv. Significant differences between the enrichment ratio of each nutrient in ryegrass cv. Lema and guava cv. Paluma leaves were identified by non-parametric Mann–Whitney Rank Sum Test, based on the enrichment ratio calculated in the different exposure experiments. These comparisons allowed identifying which nutrients were more strongly accumulated in the leaves of each biomonitor species, allowing performing the next step of data treatment that focused on the evaluation of spatial and seasonal variations in the nutritional enrichments within the study region. Thus, new background values (bve), now based on the

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enrichment dataset and the nutritional preferences of each accumulator species, were estimated as previously described. As expected, bve was approximately equal to one in all nutrients. Assuming that the higher the ER values above bve, the higher the contamination risk, a scale was suggested to classify the regional contamination risk by each element during the experimental period following the method adopted by Klumpp et al. (2006), with necessary adaptations. This procedure allowed classifying the contamination risk in all sites and during all the exposure experiments in the following four degrees: I – non-contamination risk (enrichment ratio of a nutrient r bve); II – low contamination risk (enrichments higher than bve and lower than bve plus three times the standard deviation); III – high contamination risk (enrichments higher than bve plus three times the standard deviation and lower bve plus six times the standard deviation); and IV – distinctly high contamination risk (enrichments Zbve plus six times the standard deviation). A Principal Component Analysis (PCA) was performed with ER dataset of both accumulator species, transformed by ranging, aiming to summarize the total variability of the data and to highlight the suitability of each species for biomonitoring seasonal and spatial contamination risks posed by anthropogenic nutrient deposition due to air pollution in the study region, which is characterized by marked dry and wet seasons. In addition, aiming to detect eventual nutritional imbalances, concentration ratios between nitrogen and phosphorus (N/P) or sulfur (N/S) were calculated only for ryegrass cv Lema, since the N content in its leaves exceeded the bve in greater proportion than that found in guava ‘Paluma’ leaves (see more details in Section 3). Non-parametric analyses identified significant differences in the nutritional enrichments, N/P and N/S among exposure sites (Kruskal–Wallis One Way Analysis of Variance on Ranks) and wet and dry seasons (Mann–Whitney Rank Sum Test), also based on data from different exposure experiments. All the results (nutrient concentrations, enrichment ratios, N/P and N/S) are presented as box plots. Each plot shows the 25th to 75th percentiles of the original datasets (rectangles), the medians (horizontal line dividing the rectangles), the error bars and the outlier values (●). The results from each exposure experiment were individually included in such type of graphic presentation, allowing showing all the data variability during the long experimental period and the application of non-parametric statistics to check overall tendencies.

3. Results and discussion 3.1. Abiotic conditions during the experimental period Environmental parameters varied characteristically among wet and dry seasons, in all three years of biomonitoring, resembling the yearly seasonal pattern previously described in the region by CETESB (2013) and Alvares et al. (2014). Higher values of meteorological variables were measured during the wet seasons (spring and summer), notably rainfall, which significantly contributes to define the climatic typology in the MRC ((Fig. 1). The climate in the region is predominantly Cwa according to Koeppen’s classification (humid subtropical zone with dry winter and hot summer) (Alvares et al., 2014). Monthly total rainfall and mean temperature generally reach 200 mm and 24 °C, respectively, during the wet season (from October to March) and drop down to 30 mm and 20 °C during the dry season (from April to September), respectively. In opposition to the meteorological variables, monthly mean values of nitrogen and sulfur dioxide and particulate material that may carry different macro and micronutrients were

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Fig. 2. Box plot representation of the concentration ranges and respective enrichment ratios relative to background values (red symbols) in leaf samples of ryegrass cv. Lema (A) and guava cv. Paluma (B) throughout all the experimental period. Values greater than one (indicated by the red line) denote enrichment. n indicates significant higher enrichment ratio of a nutrient in one accumulator species in comparison to that estimated in the other species (p o0.05, Mann–Whitney Rank Sum Test). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

distinguishably higher during the dry seasons (Fig. 1). Maximum mean values of 63 μg NO2 m  3, 30 μg SO2 m  3 and 94 μg PM10 m  3 were recorded during the dry season. By contrast, lower concentrations were measured during the wet season (45 μg NO2 m  3, 24 μg SO2 m  3 and 63 μg PM10 m  3). In fact, the concentration of air pollutants in the MRC is directly influenced by the predominant weather conditions, in addition to the distribution and intensity of pollutant emissions and topography. As a rule, the highest concentrations of pollutants occur, except ozone, from April to September (dry season), due to the higher occurrence of thermal inversions at low atmosphere levels, high percentage of slight winds and low rainfall (Boian and Andrade, 2012; CETESB, 2013). 3.2. Comparing nutrient accumulation potential of ryegrass cv. Lema and guava cv. Paluma The concentrations and the background values in ryegrass cv. Lema and guava cv. Paluma decreased similarly according to the following order of magnitude: K4N 4Ca 4S4 P4Mg 4Fe4 Mn 4B 4Zn 4Cu (Fig. 2). The minimum and maximum concentrations of macronutrients in ryegrass cv. Lema ranged from 0.5 g kg  1 of Ca to 131.0 kg  1 of K, respectively, and in guava cv. Paluma from 1.2 kg  1 of Mg and S to 76.5 g kg  1 of K. The minimum and maximum concentrations of micronutrients in ryegrass

cv. Lema ranged from 0.001 g kg  1 of Cu to 2.13 g kg  1 of Fe and in guava cv. Paluma from 0.001 g kg  1 of Cu to 1.3 g kg  1 of Fe (Fig. 2). The background concentrations of N, P, K, Mg, Cu and Fe tended to be higher in ryegrass cv. Lema than in guava cv. Paluma, whereas the background concentrations of Ca, B and Mn found in guava cv. Paluma were higher than in ryegrass cv. Lema (Fig. 2). Nakazato (2014) worked around a petrochemical industry in Cubatão region (SE Brazil) and found higher background values of N and K in ryegrass cv. Lema and of K and Zn in guava cv. Paluma than those estimated in the current study. In addition, the concentrations of most of the nutrients measured in several single samples of both ryegrass cv. Lema and guava cv. Paluma were above the respective background values, indicating that these samples were enriched by these nutrients (Fig. 2), similarly to the results found by Nakazato (2014). Therefore, the estimate of enrichment ratios in relation to background concentrations would give a more reliable overview of the biomonitor plants accumulation capacity and their suitability for biomonitoring purposes than of the proper leaf concentrations, as discussed in other biomonitoring studies (Domingos et al., 1998; Moraes et al., 2002; Perry et al., 2010). In fact, ER 41 was frequently estimated during the experimental period for all nutrients in leaf samples of both bioacumulator species (Fig. 2). Ryegrass cv. Lema plants showed significantly higher enrichments of N (median ERN ¼0.92), Mg (median ERMg ¼1.03), Fe

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Fig. 3. Principal Components Analysis (PCA) summarizing the nutritional enrichment ratios in both accumulator species. The table shows the correlation coefficients of each variable with the most explicative principal components (PC 1 to 3). Abbreviations: L – sampling unities of ryegrass cv. Lema; P – sampling unities of guava ‘Paluma’; d – dry season; w – wet season. K – potassium; N – nitrogen; Ca – calcium; S – sulfur; P – phosphorus; Mg – magnesium, Fe – iron; Mn – manganese; B – boron; Zn – zinc; Cu – copper.

(median ERFe ¼1.21), Mn (median ERMn ¼1.06) and Cu (median ERCu ¼0.91) than guava cv. Paluma plants (median ERN ¼0.90, ERMg ¼0.87, ERFe ¼ 1.04, ERMn ¼0.98, ERCu ¼0.90). On the other hand, the last species presented higher ability to accumulate K (median ERK ¼0.93), Ca (median ERCa ¼ 0.89), P (ERP ¼1.06) and B (ERB ¼0.81) over the background levels than ryegrass cv. Lema (median ERK ¼ 0.88, ERCa ¼ 0.88, ERP ¼0.84, ERB ¼0.76). No significant differences were found between the capacities of both accumulator species to enlarge S and Zn concentrations in the leaves over the respective bv (Fig. 2). Nakazato (2014) also found higher enrichments of Mg, Fe, Cu, S and Zn in ryegrass cv. Lema and of B, Fe, N and P in guava cv. Paluma (Fig. 2). The author associated N, S, P, Fe, B and Zn to oil refinery emissions and Mg to sea salt that comes from the Atlantic Sea. The Principal Component Analysis (PCA) performed with enrichment values highlighted the differences between species exposed in different seasons and allowed seeing the species affinity

to certain elements (Fig. 3). The analysis showed that 67% of the variability of data from both ryegrass cv. Lema and guava cv. Paluma were summarized in the first 3 axes (Fig. 3). Sampling units of ryegrass cv. Lema exposed during the wet season were more related to high concentration of N (positive side of axis 2), Mg and Cu (positive side of axis 3), and sampling units of plants exposed in the dry season were more related to high concentration of Fe (negative side of axis 1) and S (negative side of axis 2) (Fig. 3). Sampling units of guava plants exposed during the wet season were associated to higher values of K and P (positive side of axis 1). Guava cv. Paluma exposed during the dry season showed low correlation with all elements (Fig. 3). 3.3. Spatial and seasonal nutritional enrichments in the study region based on leaf accumulation According to the data treatment planning, the evaluation of

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Fig. 4. Boxplot representation of enrichment ratios in leaf samples of ryegrass cv. Lema exposed in different sites in MRC during wet and dry seasons. I1, I2, and I3 – industrial areas; I/A – industrial and agricultural areas; A1, A2, A3, A4, A5, A6 and A7 – agricultural areas; A/U – agricultural and urban areas; U1 and U2 – urban areas. n indicates significant higher enrichment ratios in one season in comparison to the other (p o0.05; Mann–Whitney Rank Sum Test). Contamination risk classification: I. Noncontamination; II. Low contamination; III. Elevated contamination; IV. Distinctly elevated contamination.

spatial and seasonal variations in the nutritional enrichments in the study region (Figs. 4–6) was based on the results of the mentioned statistical comparisons between cultivars. Although significant differences were not proved between both accumulator plants for S and Zn, the ER dataset of both elements in the ryegrass cv. Lema cultures was employed to compare sites and seasons due to two reasons: (a) maximum single ER for S and Zn were calculated in ryegrass plants leaf samples (ER 44.0); (b) the ryegrass cv. Lema is indicated by VDI (2003) as a standardized biomonitor of S and metals. First, it is noteworthy that similar nutritional enrichment ratios were estimated in all sites throughout the biomonitoring period, whether ryegrass cv. Lema or guava cv. Paluma leaf samples were analyzed or not (Figs. 4 and 5). This non-spatiality may be explained by the daily wind circulation. Although the yearly wind prevailing direction (Map, supplementary material) in the MRC is southeast, the wind direction changes typically during the day: (a) the predominant wind directions are SSE and SE in early morning and evening; (b) SSE, SE and NE in the morning and (c) NNE, SSE, N, SSW and S in the afternoon. Then, prevailing winds stay between east and south during a single day (Tresmondi and Tomaz, 2004; Boian and Andrade, 2012). This typical daily wind behavior might have dispersed the air pollutants to all exposure sites, causing a uniform plant exposure to air pollutants. In addition, the regional flat topography does not offer barriers against the pollution dispersion (Boian and Andrade, 2012), favoring the mixture of pollutants in the study area. In contrast, seasonal variations in the nutritional enrichment

were evidenced by both significant differences between dry and wet seasons and distinct degrees of contamination risk estimated during the whole experimental period (Figs. 4 and 5), thus reinforcing tendencies shown by PCA analysis (Fig. 3). Significant enhanced enrichment of S and Fe (in ryegrass leaf samples) and of K and B (in guava leaf samples) were estimated during the dry seasons. We may assume that these higher ER were consequences of a greater supply of these elements to the plants during the dry seasons, when atmospheric concentrations of SO2 and particulate material containing nutrients, such as S, Fe, K and B, were also observed (Fig. 1). One probable source of Fe to ryegrass in the MRC during the dry seasons was the resuspension of oxisol soils that are rich in such element according to Lopes et al. (2015), due to the traffic in unpaved roads commonly observed in rural areas. Moreover, crop fertilization with compounds containing S, K and B in their composition and vinasse applications in sugarcane, with high K concentration (Christofoletti et al., 2013) generally occur at the end of the dry seasons, contributing to nutritional inputs and possibly imbalances to the bioaccumulator species and, by analogy, to the forest remnants that still exist in the study region. Therefore, these agricultural practices may pose a contamination risk to be routinely monitored in the region. The ryegrass also revealed to be an appropriate accumulator plant of S and Fe in the study region by analyzing ER ranges. Median values of S enrichments largely reached the low contamination risk (included in class II) and many individual enrichment values were classified in the III and IV degrees (high or distinctly high contamination) in most sites. Most of the Fe

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U2 U1 A/U A7 A6 A5 A4 A3 A2 A1 I/A I3 I2 I1

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U2 U1 A/U A7 A6 A5 A4 A3 A2 A1 I/A I3 I2 I1

3

sites

sites

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sites

sites

I

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4

5

phosphorus

II

III

IV *Dry

U2 U1 A/U A7 A6 A5 A4 A3 A2 A1 I/A I3 I2 I1 U2 U1 A/U A7 A6 A5 A4 A3 A2 A1 I/A I3 I2 I1

Wet 0

1

2

3

boron

Fig. 5. Boxplot representation of enrichment ratios in leaf samples of guava cv. Paluma in different sites in MRC during wet and dry seasons. I1, I2, and I3 – industrial areas; I/ A – industrial and agricultural areas; A1, A2, A3, A4, A5, A6 and A7 – agricultural areas; A/U – agricultural and urban areas; U1 and U2 – urban areas. n indicates significant higher enrichment ratios in one season in comparison to the other (p o 0.05; Mann–Whitney Rank Sum Test). Contamination risk classification: I. Non-contamination; II. Low contamination; III. Elevated contamination; IV. Distinctly elevated contamination.

enrichment median values were included in the high contamination class (III), and a large amount of enrichment values reached distinctly high contamination risk (degree IV), such as in the urban site U2, located in Paulínia city (Fig. 4). The ryegrass plants exposed in this urban site also tended to accumulate Zn and Cu during the dry season, indicating distinctly high contamination in some exposure experiments (Fig. 4). These tendencies observed in U2 site may be associated with emissions of particulate matter

containing these elements from the petrochemical industries and traffic of vehicles (Conti et al., 2009; Lehndorff and Schwark, 2010; Calvo et al., 2013; Nakazato et al., 2015). However, K enrichment in guava leaves suggested absence of contamination risk (degree I) even during the dry seasons. As for B, despite the fact that most ER were included in the first class, some single values were classified in the second degree (low contamination risk), rarely reaching higher potential

P. Bulbovas et al. / Ecotoxicology and Environmental Safety 118 (2015) 149–157

Dry

U2 U1 A/U A7 A6 A5 A4 A3 A2 A1 I/A I3 I2 I1

sites

sites

156

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* Wet

* Wet

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10

15

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25

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6

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N/P

N/S

Fig. 6. Boxplot representation of the N/S and N/P ratios in leaf samples of ryegrass cv. Lema exposed in different sites in MRC during wet and dry seasons. I1, I2, and I3 – industrial areas; I/A – industrial and agricultural areas; A1, A2, A3, A4, A5, A6 and A7 – agricultural areas; A/U – agricultural and urban areas; U1 and U2 – urban areas. n indicate significant difference between wet and dry seasons (p o 0.05, Mann–Whitney Rank Sum Test).

contamination level in the U2 urban site (elevated contamination or distinctly elevated contamination risks, respectively) (Fig. 5). Mn, Cu and Zn were proportionally more concentrated than the respective background values and N/S and N/P ratios were higher in ryegrass exposed during the wet season (Figs. 4 and 6). Mn was the most enriched element in ryegrass plants during the wet season. Most median ER were classified in the second contamination degree and a considerable number of ryegrass samples accumulated more than twice Mn when compared to the background concentration, indicating high to distinctly high contamination risks in all MRC sites (III and IV degrees, respectively). The dataset of Cu and Zn enrichments were mainly classified between degrees I and II; only few enrichment values were included in the 3rd and 4th contamination risk classes (Fig. 4). Although Mn, Cu and Zn are essential and non-toxic in low concentrations to plants, their levels may increase in a polluted environment due to atmospheric deposition derived from vehicular traffic (Conti et al., 2009; Klumpp et al., 2009; Guzmán-Morales et al., 2011), also increasing the possibility of toxic effects on living organisms. Therefore, Mn toxic effects might be more probable than those of Cu and Zn in the MRC. According to Klumpp et al. (2009), the maximum Cu and Zn values measured in ryegrass plants exposed in the MRC (0.064 g kg  1 and 0.158 g kg  1, respectively) were far below the recommended limits for animal feed, contrasting with other biomonitoring studies. For example, high concentrations of Cu and Zn and other traffic-related elements were observed in ryegrass cv. Lema after exposure in Spanish cities (Klumpp et al., 2009). It was also observed in Tillandsia capillaries exposed in Cordoba, Argentina (Abril et al., 2014). The ryegrass plants tended to accumulate more nitrogen during the wet season, an expected result if we consider that water plays an important role in the nitrogen uptake by plants, and thus in the absorption of other nutrients (Artur et al., 2014). These authors found significant interaction between nitrogen and sulfur rates in

terms of the amount of water consumed by Brachiaria brizantha plants. They reasoned that the sulfur required by plants, although small, is closely related to the nitrogen absorption and the metabolism in plants. It explains why high ratios between nitrogen and sulfur were found during the wet seasons (Fig. 6), periods when higher water availability and lower SO2 concentration were observed (Fig. 1). High N/P ratios were consequences of high N concentrations and/or low P levels in ryegrass cv. Lema exposed in the field during the wet seasons (Fig. 6). Huang et al. (2012) stated that several species have leaf contents of N and P positively correlated in a highly significant level, in order not to limit their productivity. However, this association was not proved in the present study, as shown by the PCA analysis (Fig. 3). The P and N vectors positioned on the opposite sides of axis 1 indicated that the stoichiometric balance between both elements was changed by increases in the atmospheric deposition of N compounds possibly of anthropogenic origin. In fact, depending on the intrinsic features of species, the high N availability in the environment does not ensure the high accumulation of other elements (Güsewell, 2004), including P. Thus, the N/P ratio in leaves was also a measurement of the potential limitation of P not only to bioindicator plants, but also to crops and native plants of forest ecosystems in the MRC, according to Huang et al. (2012).

4. Conclusions The results led us to the following conclusions: (a) Significantly higher enrichment ratios (ER) pointed that ryegrass cv. Lema was the most appropriate accumulator species for biomonitoring the contamination risk associated with N, S, Mg, Fe, Mn, Cu and Zn deposition from several emission sources in the MRC, such as vehicular traffic, petrochemical industries and agricultural practices; (b) Significantly higher enrichment ratios also revealed that

P. Bulbovas et al. / Ecotoxicology and Environmental Safety 118 (2015) 149–157

the guava plants were the most appropriate accumulator species for biomonitoring K, Ca, P and B deposition originated from crop fertilization procedures, such as the vinasse application in extensive sugarcane plantations, which is rich in K; among other nutrients; (c) Based on the mentioned biomonitoring capacities of both accumulator species, we may state that the nutrient deposition associated with air pollution is spatially homogeneous in the entire study area; (d) In contrast, clear seasonality in the contamination risk by nutritional inputs were evidenced by both accumulator cultivars, either in response to strong climatic seasonality that influence air pollution dispersion or to specific agricultural practices; significantly higher contamination risk by S, Fe (indicated by ryegrass plants), K and B (indicated by guava plants) occurred during the dry season; enhanced contamination risk indicated by higher ER of Mn, Cu and Zn, as well as of N/S and N/P ratios in ryegrass cv. Lema leaf samples were highlighted during the wet season.

Acknowledgments The authors thank Programa SISBIOTA-BRASIL (proc. CNPQ 563335/2010; proc. FAPESP 2010/52319-2) for financial support. The Refinaria de Paulínia (REPLAN), Usina Ester, Fazenda São José, Sítio Americana, Cooperativa Agropecuária Holambra, Haras Patente, sítio Cosmópolis, Áreas de Relevante Interesse Ecológico “Mata da Santa Genebra”, Prefeitura de Paulínia, Companhia de Saneamento Básico do Estado de São Paulo (SABESP) for permitting the plant exposure in their own areas; Norddeutsche Pflanzenzucht HansGeorg Lembke KG (NPZ-Lembke) for donating seeds of ryegrass cv. Lema Coordenação Especial para Restauração de Áreas DegradadasCERAD and Paulo R.T. Ortiz for designing Map (supplementary material); Amariles C. de Souza, Andressa R. dos Santos, Cristiane Aguiar Silva, Francisco R. da Silva, Leonardo K. Fujita, Patricia Giampaoli, Solange E. Brandão, and Valdenice S. Amorim, for technical assistance.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.ecoenv.2015.04. 024.

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