Urban Forestry & Urban Greening 54 (2020) 126780 Contents lists available at ScienceDirect Urban Forestry & Urban Greening journal homepage: www.elsevier.com/locate/ufug Leaf traits of Quercus ilex L. affect particulate matter accumulation a a a b,c Francesco Esposito , Valeria Memoli , Speranza Claudia Panico , Gabriella Di Natale , Marco Trifuoggib,c, Antonella Giarrab,c, Giulia Maistoa,* a b c T Dipartimento di Biologia, Università degli Studi di Napoli Federico II, Via Cinthia, 80126, Napoli, Italy CeSMA-Centro Servizi Metrologici e Tecnologici Avanzati, Università degli Studi di Napoli Federico II, Via Cinthia, 80126, Napoli, Italy Dipartimento di Scienze Chimiche, Università degli Studi di Napoli Federico II, Via Cinthia, 80126, Napoli, Italy A R T I C LE I N FO A B S T R A C T Handling Editor: A. Alessio Fini In urban areas, particulate matter (PM) is the most abundant airborne pollutant. Plants have been reported to filter PM, as leaves may intercept and adsorb it. The aims of the research were: i) to evaluate if leaves of Quercus ilex L., an ornamental species proven to be a good monitor of air quality, of different ages (1 and 2 years old) differed for the main leaf traits; ii) to assess the efficiency of Q. ilex L. leaves of different ages to intercept particulate matter of two sizes (PM > 10 and PM10); iii) to highlight the leaf traits that enhanced the accumulation of PM > 10 and PM10 on leaf surface. The research was performed at four municipalities on the outskirts of Naples (Southern Italy). In April 2018, Q. ilex L. leaves of one and two years old were collected and then described for length, width, area, thickness, circularity, dry matter content and petiole length. The tested hypotheses were: older leaves, that should have high values of the investigated leaf traits, intercept and accumulate greater amounts of PM; leaves with greater circularity, width and length, and with lower dry matter content are expected to accumulate more PM. The findings highlighted that Q. ilex leaves of different ages did not statistically differ neither for the investigated leaf traits nor for the amounts of accumulated PM > 10 and PM10; the greater amount of PM was observed in Q. ilex leaves with higher circularity and lower dry matter content; smaller width leaves seem to favour the accumulation of PM > 10 and those with smaller length the accumulation of PM10. Keywords: Leaf dry matter content Leaf circularity Leaf size One- and two-years old leaves PM > 10 and PM10 1. Introduction Recently, a general deterioration of air quality, due to high concentrations of pollution, is observed in urban areas (Sawidis et al., 2011). Among the various airborne pollutants, particulate matter (PM) is the most abundant (Dzierżanowski et al., 2011) and consists in a mixture of black carbon, soil, heavy metals and other substances (Bell et al., 2011; Mori et al., 2018). PM is emitted in atmosphere by both anthropogenic (i.e., industrial processing, road dust and vehicle exhausts) and natural sources (i.e., volcanic eruptions, soil and rock erosions). Besides, PM is considered the most threatening as it can cause many diseases to human health such as hypertension, heart disorders, allergies and asthma (Atkinson et al., 2001; Manes et al., 2016). A consequence of intensive urbanization and industrialization, due to the increasing human population (Guo and Maghirang, 2012; Morakinyo and Lam, 2016), is the exposure of people of air PM that exceed the annual threshold values equal to 20 μg m−3 for PM10 and 10 μg m−3 for PM2.5 (WHO, 2016). In urban areas, plants have been reported to filter air pollutants, as ⁎ leaves show high capability to intercept and adsorb PM (Manes et al., 2016; Popek et al., 2017). For instance, Yang et al. (2005) estimated a reduction, by trees, of 772,000 kg of PM10 per year in the downtown Beijing (China) and Nowak et al. (2014) concluded that urban vegetation could remove 17.4 million tonnes of PM10 per year in the United States of America. More recently, Yin et al. (2011) found that air particulate matter decreased by, approximately, 9 % at distances of 50–100 m from various urban emission sources due to urban vegetation; so, they concluded that pollutant diffusion distance and crown volume coverage of urban vegetation could be key predictors of air pollutant removal rate. PM can deposit on the leaves by sedimentation, diffusion or turbulent transfer, resulting in impaction and interception (Freer-Smith et al., 2005; McDonald et al., 2007). However, PM accumulation in the leaves mainly depends on their characteristics such as presence of trichomes, surface roughness, epicuticular wax layer, and leaf shape and size (Dzierżanowski et al., 2011; Weerakkody et al., 2018a). In fact, Weerakkody et al. (2018a) in an experiment performed with synthetic leaves, observed the highest PM density on the smallest leaves. Besides, Corresponding author. E-mail address: g.maisto@unina.it (G. Maisto). https://doi.org/10.1016/j.ufug.2020.126780 Received 21 November 2019; Received in revised form 9 May 2020; Accepted 30 June 2020 Available online 06 July 2020 1618-8667/ © 2020 Published by Elsevier GmbH. Urban Forestry & Urban Greening 54 (2020) 126780 F. Esposito, et al. 2.2. Leaf functional traits Esposito et al. (2019a) highlighted that leaf width and the petiole length affect PM interception and heavy metal accumulation. Finally, Leonard et al. (2016) report that lanceolate leaves intercept more PM than leaves with other shapes. In contrast, it is still poorly known if other leaf traits, such as dry matter content or thickness, can affect PM interception; although some authors report that leaves with low dry matter content, being more flexible and fluttering, may intercept high amount of air deposition (Gillies et al., 2002). PM deposition and its interception by plants can be affected by many factors categorized into two groups: external and internal factors (Xie et al., 2018). The external factors include the particle concentration and size, and the meteorological elements such as temperature, humidity, wind speed and direction (Cai et al., 2017; Prusty et al., 2005; Xie et al., 2018). The internal factors include the plant structural and functional characteristics such as canopy morphology, leaf density and surface (Dzierżanowski et al., 2011; Leonard et al., 2016; Xie et al., 2018). In the Mediterranean region, where urbanization is intensive Q. ilex L. is used as an ornamental species and has proven to be a good monitor of air quality as its capability to accumulate trace metals and polycyclic aromatic hydrocarbons (De Nicola et al., 2008, 2014, 2017; Esposito et al., 2019a, 2019b; Maisto et al., 2013a, 2013b; Memoli et al., 2019; Sgrigna et al., 2015). The relationship between pollutant contents in Q. ilex leaves and seasonality is well known (Alfani et al., 2005; De Nicola et al., 2011); whereas the relationship between leaf pollutant accumulation and leaf age is more controversial (De Nicola et al., 2003; Esposito et al., 2019b). The current knowledge about the capability of young leaves of Q. ilex to provide a significant contribution to air cleaning is missing. Therefore, the aims of the research were: i) to evaluate if Q. ilex L. leaves of different ages (1 and 2 years old) differed for the main leaf traits; ii) to assess the capability of Q. ilex L. leaves of different ages to intercept particulate matter of two sizes (PM10 and PM > 10); iii) to highlight the leaf traits that enhanced the accumulation of PM10 and PM > 10 on leaf surface. To achieve the aims, the following hypothesis was tested: older leaves, having high values of the investigated leaf traits, intercept and accumulate greater amounts of PM; leaves with greater circularity, width and length, and with lower dry matter content are expected to accumulate more particulate matter. The leaf functional traits were evaluated on 70 leaves of each age, with the exception of leaf dry matter content that was evaluated on 30 leaves. Leaf length and width, the leaf area and the petiole length were determined according to Esposito et al. (2019a) and using the program Image J 1.45 (Image Analysis Software). Leaf circularity was calculated according to Min et al. (2018), as reported below: Circularity = [4π × (area / perimeter2)] Leaf dry matter content was calculated according to Arena et al. (2017), as reported below: Dry matter content = dry matter weight / turgid weight Leaf thickness was evaluated through a micrometer according to Perez-Harguindeguy et al. (2013). 2.3. PM amount Seventy leaves of each age were used for determination of PM amount. The procedure adopted for quantification of atmospheric particulate deposit on the leaves is similar to Dzierżanowski et al. (2011). Each sample of leaves was placed in a glass beaker and washed by four consecutive shakings with 250 mL of deionized water (each lasting 20 min) in order to wash off particles from leaf surfaces. The water was then filtered with a filtration apparatus with vacuum pump, on pre-weighed filters through analytical balance with a resolution of 0.01 mg up to constant weight and were weighed after filtration after drying at 105 °C. According to Dzierżanowski et al. (2011), Whatman™ Grade 41 paper filters (Type 91: retention PM > 10 μm) were used to evaluate particulate matter, in washing waters, with geometrical diameter greater than 10 μm (PM > 10) and subsequently, Millipore Membrane paper filters (Type 42: retention between 2.5 μm and 10 μm) were used to evaluate particulate matter, in washing waters, with geometrical diameter smaller than 10 μm (PM10). Then, the filters were dried at 105 °C for two hours, to calculate the mass of PM10 PM > 10 in each leaf sample. The values were normalized per unit of area (μg cm−2). 2. Materials and methods 2.4. Statistical analyses 2.1. Study area and sampling The coefficient of variation (CV) was calculated as percentage of ratio between standard deviation and mean value of each leaf trait for both the leaf ages (1y and 2y). The normality of the data distribution was assessed by the ShapiroWilk test and the data were normalized by logarithmic transformation. The paired t-test was performed in order to evaluate the differences in leaf traits and in each PM typology (PM10 or PM > 10) according to leaf ages (1y and 2y) as well as in order to evaluate the differences between PM10 and PM > 10 for each leaf age (1y or 2y). The stepwise regressions were performed in order to evaluate the dependence of PM (PM10 or PM > 10) accumulated on the leaves of both the ages (1y or 2y) and the leaf traits. The statistical tests were performed by the Systat_SigmaPlot_12.2 software (Jandel Scientific, San Rafael, CA, USA) and were considered statistically significant at least for P < 0.05. The research was performed at four municipalities (Mariglianella, Brusciano, Castello di Cisterna and Pomigliano d’Arco) on the outskirts of Naples, Southern Italy (Fig. 1). The Italian Legislative Decree 155/10 has fixed threshold values for air PM concentrations (the mean daily air concentrations of PM10: 50.0 μg m−3) and number of daily exceedances (35 days a year). Over the four months before the leaf sampling, for the whole investigated area, the mean daily air concentration of PM10 was 50.8 μg m-3 with a number of daily exceedances of 44 (www. arpacampania.it). The sampling of leaves was performed in April 2018, before bud break that for Q. ilex L. occurs in May (De Lillis and Fontanella, 1992), picking them from the ultimate and the penultimate internodes (approximately, one and two years old, respectively) of the same branches at 2 m above the ground. In order to obtain a sample of leaves representative of the air PM deposition, the leaves were collected from the outer part of the canopies and from the four sides (north, south, east and west). At each site, from 40-year old specimens (at least eight for each site), 100 expanded leaves of each age (1y and 2y) without damage to the lamina were sampled by hand taking care to minimize the contact with the leaf surfaces (Alfani et al., 2000, 2005). In laboratory, the collected leaves were divided into two subsamples: 30 leaves were used to evaluate the leaf dry matter content and the remaining 70 leaves were used to evaluate the other functional traits and to measure the PM amount. 3. Results The values of leaf area and thickness were slightly higher in 1y (leaf area: 14.6 ± 1.60 cm2 and thickness leaves: 0.29 ± 0.01 mm) than in 2y (leaf area: 13.6 ± 1.96 cm2 and thickness leaves: 0.28 ± 0.01 mm) leaves, but were not statistically significantly different (Fig. 2). By contrast, the values of leaf length, width, petiole length, circularity and leaf dry matter content were slightly lower in 1y (in 1y leaves, leaf 2 Urban Forestry & Urban Greening 54 (2020) 126780 F. Esposito, et al. Fig. 1. Map and geographic coordinates of the sampling sites. developed after a year and secondly, that they were affected to a similar extent by the overall environmental conditions (Arena et al., 2014; Esposito et al., 2019b; Guerin et al., 2012). The amount of particulate matter (both PM10 and PM > 10) on the leaf surfaces would seem largely dependent on environmental conditions occurring at the investigated sites as opposed to the time the leaves were exposed, as no statistically significant differences were observed between 1y and 2y leaves. In particular, climatic phenomena such as the occurrence of heavy rain or strong wind are reported as responsible for removal or re-suspension of particulate matter from leaf surfaces in different plant species (Wang et al., 2015; Weerakkody et al., 2018b). These climatic phenomena likely can be responsible for the comparable amounts of both PM10 and PM > 10 in the investigated 1y and 2y leaves. Anyway, saturation phenomena could be not excluded. In fact, Wang et al. (2015) observed that the particulate deposition on leaf surface was significantly affected by the exposure period, as notwithstanding the maximum accumulation of PM10 was detected on the day 28 after heavy rain, its peak of accumulation occurred on the day 10, suggesting a saturation of the leaf lamina already after ten days. Besides, Beckett et al. (2000) report that the reduction of the leaf adhesion surfaces can cause a bounce-off the particles. A key role in PM load on foliage is given by deposition velocity and capturing efficiency. In fact, turbulent airflow and associated impaction are the main mechanisms resulting in the greater deposition of PM on larger than shorter leaves. The inertia of particles, travelling in an air stream and curving around leaf, forces them through the boundary layer and onto the leaves (Gregory, 1973). In addition, the canopy effect highlighted by De Nicola et al. (2011) for accumulation of polycyclic aromatic hydrocarbons in Q. ilex leaves could be responsible of the lack of statistically significant differences of particulate matter amount between 1y and 2y leaves. Likely, the oldest leaves could intercept less airborne particulate than the youngest ones, as they were partially sheltered. A reduction of the adhesion surfaces, due to the presence of a large number of particles bound to the leaf trichomes and epicuticular waxes, can be supposed in the investigated 1y leaves (De Nicola et al., 2005). length: 5.87 cm ± 0.26, leaf width: 2.72 ± 0.26 cm, petiole length: 0.97 ± 0.05 cm, leaf circularity: 0.60 ± 0.01 and leaf dry matter content: 0.50 ± 0.01 g g−1; in 2y leaves, leaf length: 6.07 ± 0.22 cm, leaf width: 2.75 ± 0.19 cm, petiole length: 1.01 ± 0.06 cm, leaf circularity: 0.62 ± 0.01 and leaf dry matter content: 0.51 ± 0.01 g g−1), although the differences were not statistically different (Fig. 2). As the leaf traits did not statistically vary between 1y and 2y leaves, the coefficients of variation (CV) were calculated, in order to estimate the variability inside each the leaf trait, taking into account all the values independently from the leaf age. The CVs for circularity and leaf dry matter were, respectively, 4.20 and 5.43 %, those of leaf length and thickness were, respectively, 10.6 and 12.1 %, that of petiole length was 12.5 %, that of leaf width was 20.2 % and that of leaf area 31.1 %. The amounts of PM10 and PM > 10 were slightly higher in 1y (PM10: 35.0 ± 8.86 μg cm−2 and PM > 10: 481 ± 216 μg cm−2) than in 2y (PM10: 32.9 ± 3.13 μg cm−2 and PM > 10: 331 ± 57.5 μg cm−2) leaves and the differences were not statistically different (Fig. 3). However, for the leaves of the same age, the amount of PM > 10 was statistically (P < 0.001) higher than that of PM10 (Fig. 3). The stepwise regressions showed that the amount of PM > 10 was negatively affected by leaf width and leaf dry matter content and positively affected by circularity (Table 1); however, the amount of PM10 was negatively affected by leaf length and leaf dry matter content and positively affected by circularity (Table 1). 4. Discussion 4.1. Leaf traits and particulate matter accumulation in Q. ilex leaves of different ages The values of all the leaf traits, with the exception of thickness that was higher, were comparable to those reported by other authors for Q. ilex leaves of urban areas (Arena et al., 2014, 2017; Esposito et al., 2019a, 2019b; Muhammad et al., 2019). The lack of statistically significant differences of the leaf traits between leaves of different ages (1y and 2y), firstly, suggests that the younger leaves were already fully 3 Urban Forestry & Urban Greening 54 (2020) 126780 F. Esposito, et al. Fig. 3. Mean values ( ± s.e.) of PM > 10 (empty bars) and PM10 (hatched bars) in Q. ilex L. leaves of one (white bars) and two (grey bars) years old (number of leaves for each age = 70). Asterisks indicate statistically significant differences between PM > 10 and PM10 in leaves of the same age, upper-case letters indicate statistically significant differences of PM > 10 between different ages and lowercase letters indicate statistically significant differences of PM10 between different ages. * P < 0.05, ** P < 0.01 and *** P < 0.001. Table 1 Stepwise regressions between the intercepted PM > 10 or PM10 (dependent variables) and the investigated leaf traits (independent variables). The first numbers represent the intercepts of the regression lines, whereas the numbers in brackets represent the contributions of each independent variable (leaf length, width, circularity and dry matter content - LDMC) in the variation (positively or negatively expressed) of the dependent variables. Model R2 P PM > 10 = 2.851 - (2.141 x leaf width) + (8.485 x circularity) – (8.203 x LDMC) PM10 = 2.781 - (1.936 x leaf length) + (4.238 x circularity) – (3.864 x LDMC) 0.819 0.02 0.870 < 0.001 The greatest accumulation of PM > 10 as compared to PM10 could be due to the high presence in the atmosphere of the investigated area of coarse (PM > 10 and PM10) particulate likely linked to both natural and anthropogenic sources (Chow et al., 2006). In fact, it is widely reported that coarse particulate matter is mainly associated with the re-suspension of crustal mineral dust from fields or bare soils by local winds action (Belis et al., 2013; Querol et al., 2008), but they can be also associated to fuel exhausts not completely combusted (Belis et al., 2013). These suppositions are corroborated by the characteristics of the investigated sites that are surrounded by wide crop fields and are high densely populated and then affected by numerous anthropic sources such as vehicular traffic, domestic heating and small factories. In addition to the contribution of the emission sources, also the different weights of the particulate matter of different sizes (PM > 10 and PM10) could be the responsible of the greater amounts of PM > 10 on the investigated Q. ilex leaves. In fact, Ottelé et al. (2010) report, in a visual study count of PM on leaves of H. helix, that the large particles (≥ 10 μm) are more rare than the smaller ones (< 10 μm). Although the amount of PM10 on the investigated Q. ilex leaves were lower of PM > 10, it was higher than that measured by Sgrigna et al. (2015) on leaves of the same species collected in the industrial city of Terni (central Italy), suggesting a contamination of the air also by fine particulate in the studied area. Fig. 2. Mean values ( ± s.e.) of leaf length, leaf width, leaf area, leaf thickness, petiole length, leaf circularity and leaf dry matter content in Q. ilex L. leaves of one (white bars) and two (grey bars) years old (number of leaves, for each age, used to evaluate the leaf dry matter content = 30; number of leaves, for each age, used to evaluate the other leaf traits = 70). 4 Urban Forestry & Urban Greening 54 (2020) 126780 F. Esposito, et al. thank Mrs. Roberta Leandri for English revision. 4.2. Relationships between leaf traits and particulate matter accumulation in Q. ilex leaves Appendix A. Supplementary data The amount of PM intercepted and accumulated on Q. ilex leaves would seem to be linked to some of the investigated leaf traits, such as leaf dry matter content, circularity, width and length, as highlighted by the outcomes of the stepwise regressions. Essentially, the same patterns emerged in PM > 10 and PM10 for leaf circularity and dry matter content but differed for leaf width and length. According to Leonard et al. (2016), the findings highlighted that leaf PM accumulation was affected by the concurrence of more leaf traits rather than by each one. Leaf dry matter content and circularity would seem to play an important role in the interception and accumulation of both the PM typologies. Leaves with higher dry matter content tend to be physically stronger and relatively tough (Pérez-Harguindeguy et al., 2016) as a consequence, leaves with lower dry matter content are more flexible and fluttering allowing to a major interception of the atmospheric dust (Gillies et al., 2002; Weerakkody et al., 2018b). By contrast, leaves tending to the circular shape result aerodynamically more stable and, in turn, enhance the PM interception and accumulation (Miri et al., 2018). In addition, PM accumulation was also enhanced for smaller (in terms of length and width) leaves (Weerakkody et al., 2018a). This result also agrees with those reported by Leonard et al. (2016) who highlighted that leaves with narrower bases, compared with those with broader bases. In fact, they have higher surface specific drag, flute more erratically and then intercept less PM as well as lanceolate shaped leaves retain significantly more PM than linear or elliptical shaped ones. Besides, the findings highlighted that the accumulation of particulate matter of different sizes (PM10 and PM > 10) is also, respectively, affected by smaller width and smaller length. The present research reports innovative findings on the relationships between leaf PM accumulation and traits, as no information is still reported in the scientific literature for this species. However, the mechanisms behind these relationships are unknown. Therefore, further investigations need in order to better understand the mechanisms involved in the regulation of the relationships between these leaf traits and different kinds of PM and to study if these traits can be a leaf response to differently contaminated environments. Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.ufug.2020.126780. References Alfani, A., Baldantoni, D., Maisto, G., Bartoli, G., Virzo De Santo, A., 2000. 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Therefore, the balance between leaf flexibility and structural strength operated by circularity, that reduced the deformation and shape reconfiguration due to wind action, likely played an important role in PM interception. In addition, the innovative aspect of the present research is that Q. ilex leaves seem to show traits that can favour the interception of particulate matter of different sizes (i.e., smaller width greater amount of PM > 10 and smaller length greater amount of PM10). Declaration of Competing Interest The authors declare no conflict of interest. Acknowledgments The research was funded by MonAir Project (Monitoraggio dell’aria del Comune di Pomigliano d’Arco - NA) and by the Department of Biology of the University of Naples Federico II. The authors wish to 5 Urban Forestry & Urban Greening 54 (2020) 126780 F. Esposito, et al. 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