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Article

Particulate Pollution Capture by Seventeen Woody Species Growing in Parks or along Roads in Two European Cities

by
Irene Vigevani
1,2,3,*,
Denise Corsini
2,
Jacopo Mori
2,
Alice Pasquinelli
4,
Marco Gibin
1,
Sebastien Comin
1,
Przemysław Szwałko
5,
Edoardo Cagnolati
6,
Francesco Ferrini
2 and
Alessio Fini
1
1
Department of Agricultural and Environmental Sciences—Production, Landscape, Agroenergy, University of Milan, 20133 Milan, Italy
2
Department of Agriculture, Food, Environment and Forestry, University of Florence, 50144 Florence, Italy
3
Department of Sciences, Technologies and Society, University School for Advanced Studies IUSS Pavia, 27100 Pavia, Italy
4
R3 GIS S.r.l. NOI Techpark, 39100 Bolzano, Italy
5
Krakow Municipal Greenspace Authority (ZZM), 30-059 Kraków, Poland
6
Anthea S.r.l., 47923 Rimini, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(3), 1113; https://doi.org/10.3390/su14031113
Submission received: 9 December 2021 / Revised: 13 January 2022 / Accepted: 15 January 2022 / Published: 19 January 2022
Browse Figures
Versions Notes

Abstract

:
This research aims to extend the existing knowledge on air quality improvement by the arboreal–shrub heritage. The PM accumulation (PM10–100, PM2.5–10, and PM0.2–2.5 (µg·cm−2)) was measured with consolidated gravimetric techniques during spring, summer, and fall for 2160 leaf samples belonging to the basal, median, and apical part of the crown of 17 species located in the streets and parks of 2 European cities (Rimini and Krakow). On the same samples, the deposition (PM10 and PM2.5 (µg·cm−2·day−1)) was evaluated according to a model based on the wash-off rain effect. Quercus ilex accumulated more PMx than the other species in Rimini, while in Krakow, the highest accumulators were Pinus nigra for PM10–100, Tilia cordata for PM2.5–10, and Populus nigra for PM0.2–2.5. Only in Krakow was the capture capacity of some species affected by the street or park growing condition. The basal leaves showed greater PM10–100 accumulation than the median and apical ones. In Rimini, the total PM accumulation tended to increase throughout the year, while in Krakow, the opposite occurred. However, as the accumulation increased, the deposition decreased. The PM accumulation was reduced by rainfall and enhanced by the air PM concentration, while the wind speed effect was opposite, depending on the city. These findings are useful for directing decision makers in the design of greener, healthier, and sustainable cities.

1. Introduction

Particulate matter (PM) is the main non-gaseous pollutant in cities and consists of a dynamic and complex aggregate of organic and inorganic particles, either in a solid or liquid phase, suspended in the air [1,2]. The particles aerodynamic diameters range from 0.001 to 100 μm [3], and according to it, PM is usually divided into large (10–100 μm), coarse (2.5–10 μm), and fine (0.2–2.5 μm) [2,4,5,6], even if in the literature there are other classifications which consider ultrafine particles (<0.1 μm) [7]. The European Environment Agency listed the energy generation sector, industry, and vehicular traffic as some of the most important anthropogenic sources of PM [8]. Due to its ability to penetrate the respiratory system [9] and carry toxic compounds such as polycyclic aromatic hydrocarbons (PAH) and heavy metals (HM) [10], PM is currently considered among the most health-threatening factors in urban areas, causing more than 400,000 premature deaths in Europe [11]. Recently, the high level of PMx in the atmosphere has been considered a co-factor in the spread of COVID-19 [12], exacerbating the air quality issue worldwide.
Although current policies are trying to reduce emissions, the PM concentration is still very high, making mitigation measures urgent. PM can settle on all kind of surfaces, but plant leaves and bark were shown to be particularly effective for PM trapping [13]. All types of urban forests (peri-urban woodlands, parks, gardens, roadside trees, green roofs, and vertical greening) were shown to be effective passive biological filters against PM [14,15] while providing a wide range of co-benefits, including microclimate amelioration [16] through shading [17] and transpiration [18,19], atmospheric CO2 uptake and carbon sequestration [20], and absorption of gaseous air pollutants [21]. Although bark may also play a role [22], leaves are the plant organs considered responsible for most PM trapping by vegetation [23]. Polluting particles reach leaf surfaces through rain and snow (wet deposition) or wind force (dry deposition) [24], with the latter process being responsible for most plant capture [25]. The main mechanisms involved are gravity sedimentation, interception, Brownian diffusion, and inertial and turbulent impactions [26]. Intercepted particles can be absorbed by the leaf stomata [27] or, more frequently, retained on the surfaces until they are resuspended in the atmosphere under blowing wind, washed off by rain, or dropped to the ground with falling leaves and twigs [23,28], outlining a dynamic deposition trend [6]. Once resuspended in the air, particles can redeposit on plant organs, and once reaching the ground, organic components may be decomposed by micro-organisms, inorganic components may be immobilized in the soil, or particles can be resuspended again [27].
Many studies showed that air filtering is species-specific [4,5,6]. Consistently, trapping and the retention efficiency are not affected only by pollutant characteristics like the diameter, shape, or composition [29,30] but also by the leaf features (e.g., shape, stomata density, trichomes, cuticle ornamentations, and epicuticular waxes) [31] and conditions such as stickiness (e.g., due to the presence of honeydew [25]), wettability [32], and humidity [29]. The rougher the surface, the greater the catch. In broadleaved species, for example, the rough-surface leaves are more effective than smooth-surface ones [33]. Conifer needles or scales have been reported to be more effective than broadleaves, as they produce a thicker epicuticular wax layer with frequent longitudinal ridges which promote trapping and retention [4,34,35]. Consistently, Beckett et al. [36] found a higher deposition velocity and capture efficiency in both needle-leaved and scale-leaved species compared with broadleaves. The low tolerance of most conifers to air pollution, however, has raised concerns about the real upscalability of research findings collected in wind tunnels [36] or with small plants in environments protected from real urban conditions [6]. In addition, evergreen species, such as most conifers, have the potential to capture PM throughout the year, but on the other hand, since they keep leaves for several years, there is no possibility of recycling the accumulated particles annually, as is the case for deciduous species [27]. The effect of leaf longevity on the trapping efficiency has not been fully unraveled yet, because several investigations carried out so far evaluated the amount of foliar PMx in a single measurement, usually carried out at the end of the growing season [4,5,6,37]. Research based on seasonal sampling campaigns revealed that the leaf PM accumulation (i.e., the total amount of PM adsorbed on a leaf surface) generally increased with the leaf age [38,39], although the capture efficiency may decrease in older leaves [34].
All vegetation types can mitigate air pollution, but trees are considered the most effective for this purpose due to their large total leaf area [24] and the complex structure of their crowns, leading to turbulent air movements which increase PM trapping [40]. The importance of shrubs, however, should not be underestimated because of their canopy structure, which is often branched from the ground, and their limited height. These traits allow for designing shrub barriers very close to the source of a pollutant even in urban canyons, where PM capture can be maximized [5] without negatively impacting airflow and PM dispersion, as can occur when trees with dense canopies are planted [41,42]. It has been shown that the proximity to the pollution source increases the leaf PM accumulation [43,44]. Some studies which considered the leaf position [37,45,46] found more particles adsorbed on leaves in the lower part of the crown compared with the upper part. However, these studies investigated a maximum height of 4.0 m. Few works, to our knowledge, have reported the effect of different growing conditions (e.g., park and street) on the PM trapping capacity of the different plant species in an urban environment [37,47], and most of them are based on models [48,49].
Although research has recently focused on the assessment of the capture capacity of different species in an urban environment, there is a lack of extensive replicated measurements conducted in situ on established plants. Therefore, this research aims to evaluate PM accumulation and deposition as affected by (1) genotype, and for this purpose, 17 tree and shrub species (Acer negundo, Acer platanoides, Aesculus hippocastanum, Cornus alba, Fraxinus excelsior, Ligustrum lucidum, Pinus nigra, Pinus pinea, Platanus × acerifolia, Populus nigra, Prunus laurocerasus, Quercus ilex, Quercus robur, Sorbus aucuparia, Tilia cordata, Tilia × europaea, and Ulmus laevis) widely spread in 2 European cities (Rimini, Italy and Krakow, Poland) were used; (2) urban microclimate, and for this purpose, plants growing in parks or along streets were sampled; (3) leaf positions within the canopy, and (4) seasonality and leaf age. In this research, PM accumulation (µg·cm−2) refers to the amount of PMx adsorbed in the unit leaf area at the time leaves were sampled, and this is useful for making a relative comparison between species. PM deposition (µg·cm−2·day−1) instead refers to the change in accumulation over time, and it is useful for quantifying the amount of PMx which a species can capture in a specific time frame, such as a day, a season, or a year. For accumulation, three fractions of PM were studied (PM10–100, PM2.5–10, and PM0.2–2.5), while for deposition, only those most harmful to humans (PM10 and PM2.5) were studied. Additional aims of this research are (1) to compare the annual trend of accumulation and deposition and (2) to correlate accumulation with the meteorological (e.g., rainfall and wind speed) and environmental (PM10 and PM2.5 air concentrations) parameters. The main novelty of this research is using entire cities as living laboratories for the in situ monitoring of the contribution of established plants of some woody species arranged according to a replicated experimental design to air quality amelioration.

2. Materials and Methods

2.1. Experimental Sites

The experiment was carried out in Rimini (44°03′34″ N 12°34′06″ E, Italy), a city of about 136 km2 with about 150,000 inhabitants, and Krakow (50°03′41″ N 19°56′18″ E, Poland), a city of about 327 km2 with a population of about 780,000 people.
In Rimini, the climate is warm-temperate (Cfa, according to Köppen–Geiger classification) with an even rainfall distribution throughout the year, fairly cold winters, and hot summers. Over the last 30 years, the average minimum and maximum temperatures were 11.88 °C and 18.01 °C, and the average rainfall was 838 mm per year. Krakow enjoys a temperate climate (Cfb, according to Köppen–Geiger classification) with evenly distributed rainfall throughout the year and warm summers. Over the last 30 years, the average minimum and maximum temperatures were 4.74 °C and 12.94 °C, and the average rainfall was 835 mm per year.
In Rimini, air solid pollutants were below the critical European threshold (28.29 and 16.25 µg·m−3 for PM10 and PM2.5, respectively, as the annual average in 2018–2019) (data source: Arpae–Agenzia prevenzione ambiente energia Emilia-Romagna). Krakow instead suffers from a severe pollution load, with all the PM fractions assessed at higher concentrations compared with the EU recommendations (40 and 25 µg·m−3 for PM10 and PM2.5, respectively). Indeed, in 2019, the annual average air pollution concentration was 42.12 and 29.09 µg·m−3 for PM10 and PM2.5, respectively (data source: Główny Inspektorat Ochrony Środowiska). In the province of Rimini, the main emissions of coarse and fine PM derived from combustion processes for public and private heating (70.4% and 76.8%, respectively) and from road transport (20.6% and 16.4% for PM10 and PM2.5, respectively). A smaller share of PM emissions is linked to agricultural activities (2.9% and 1.5% for PM10 and PM2.5, respectively), air, sea, and rail transport (1.5% and 1.7% for PM10 and PM2.5, respectively), and other activities or processes (4.5% and 3.6% for PM10 and PM2.5, respectively) [50]. The largest sources of PM10 and PM2.5 emissions in Małopolskie voivodeship, the area in which Krakow is located, are the municipal and housing sectors (77% and 88%, respectively), and this is attributable to the combustion of fuels, mainly coal and wood, for heating. This is followed by emissions from other sources such as agriculture (cultivation and livestock), forests and fires (10% and 4% for PM10 and PM2.5, respectively), emissions deriving from the combustion of energy fuels and technological processes (8% and 4% for PM10 and PM2.5, respectively), and transport-related emissions (5% and 4% for PM10 and PM2.5, respectively) [51].
During the experiment, meteorological data were collected and provided by the Institute for Ubiquitous Meteorology (UBIMET), while air PM concentration data were obtained by Arpae for Rimini (Flaminia and Marecchia PM monitoring stations) and Główny Inspektorat Ochrony Środowiska for Krakow (Aleja Krasińskiego and ulica Dietla PM monitoring stations).

2.2. Plant Material and Experimental Design

Ten species per city were selected based on (1) their relevance in the existing tree inventories of Rimini and Krakow, (2) the interest of a species for municipal planting and management programs, (3) the final size at maturity, and (4) leaf deciduousness or persistence. The species monitored in Rimini were Platanus × acerifolia, Populus nigra, Quercus robur (large-sized deciduous broadleaves), Quercus ilex (large-sized evergreen broadleaf), Pinus pinea (large-sized evergreen conifer), Acer negundo, Aesculus hippocastanum, Tilia × europaea (medium-to-large-sized deciduous broadleaves), Ligustrum lucidum (small-sized semi-deciduous broadleaf), and Prunus laurocerasus (evergreen broadleaved shrub). In Krakow, the following woody species were selected: Fraxinus excelsior, Populus nigra, Quercus robur, Ulmus laevis (large-sized deciduous broadleaves), Pinus nigra (large-sized evergreen conifer), Acer platanoides, Aesculus hippocastanum, Tilia cordata (medium-to-large-sized deciduous broadleaves), Sorbus aucuparia (small-sized deciduous broadleaf), and Cornus alba (deciduous broadleaved shrub). Three species (Aesculus hippocastanum, Populus nigra, and Quercus robur) and 3 genera, although with different species (Acer platanoides, Acer negundo; Tilia cordata, Tilia × europaea; and Pinus pinea, Pinus nigra) were selected in both cities in order to allow the comparison of results.
Two city transects representative of the whole municipality were selected as experimental areas in both cities (Figure 1). Transects were stratified into two strata: (1) street (street trees, parking lots, plants near major roads, plants with a clearly delimited planting pit surrounded by pavement or buildings, or where conflicts between plants and the gray infrastructure were clearly visible) and (2) park (plants in parks, where conflicts with the built landscape were limited and where the soil around the plant was mostly unpaved).
In Rimini, the experimental areas covered 250 ha and included the Rosaspina parking lot, Palacongressi parking lot, via della Fiera (Palacongressi entrance), viale Medaglie d’Oro parking lot, via Calatafimi, via Covignano, via Milazzo, via Massaua, via Roma parking lot, via Gamedes, via Flaminia, via Lavatoio, viale Principe Amedeo, via Vittor Pisani, viale Perseo, viale Tripoli, via Melozzo da Forlì parking lot, Irnerio Bertuzzi parking lot, via Donato Bramante parking lot, via del Passero, Peep Acquario, parco Renzi, parco La Cava, parco Briolini, parco Poderi della Ghirlandetta, parco Fabbri, parco Olga Bondi, parco Alcide Cervi. In Krakow, Park Lotników Polskich (a large park located near a highly congested main road), and Planty Krakowskie (the green belt around the city center) were chosen as park areas. These were identified as extremely representative of two contrasting traffic loads typically occurring in Krakow, where high traffic around the suburbs is paralleled by low traffic in the city center, where car circulation is restricted. Street areas were selected in roads with similar land use to those surrounding the selected parks. In total, the experimental areas in Krakow covered 472 ha, including Park Lotników Polskich, Planty Krakowskie, aleja Pokoju, ulica Lema, ulica Reymonta, aleja Kijowska, ulica Mazowiecka, ulica Armii Krajowej, and ulica Warszawska.
Six replicate plots, including at least two plants of the measured species and strata, were identified within the experimental areas. One hundred twenty plants in Rimini and in Krakow were selected from the 10 model species in the above-mentioned areas for a total of 240 plants belonging to different DBH classes (Table 1).

2.3. Sampling

For PMx accumulation and deposition determination, a total of 2160 leaf samples were collected in Rimini and Krakow (1) from the 10 species selected for each city, (2) in 2 strata (street and park), (3) in 3 positions of the crown (basal, median, and apical), (4) from 3 seasons (spring, summer, and fall), and (5) from 6 replicate plants per each stratum of each model species. The leaves sampled were fully expanded and were collected in the 2 cities by carrying out 10–11 consecutive days of sampling during spring (14–24 May 2019), summer (25 June–5 July 2019), and fall (10–19 October 2018) in Rimini and spring (4–13 June 2019), summer (16–26 July 2019) and fall (10–20 September 2019) in Krakow. Sampling was conducted from 9:00 a.m. to 12:00 a.m. After dividing the live canopy into 3 portions of equal height, leaves were sampled in the lower, medial, and upper portions so that 3 samples were collected per each plant for each sampling. To access the tree canopies, an aerial work platform (AWP) was used. This made the process extremely time-consuming and required the different replicates to be sampled in different days. Care was taken to sample all species within an individual replicate on the same day. Each leaf sample (of about 300–400 cm2, the leaf area which was found to be suitable for gravimetric determination of PMx by Dzierzanowski et al. [4]) was harvested from the petioles to avoid the contact of hands with the leaf blade and stored in disposable paper bags at −20 °C to limit the deterioration of leaf tissues. Contextually with the sample collection, the plant height and height from the ground of the basal sampled leaves were measured using a clinometer (SUUNTO, Vantaa, Finland) and a laser rangefinder (Metrica, Italy), respectively. Subsequently, the height from the ground of the medial leaves was estimated.

2.4. Determination of PMx Accumulation

In this paper, the term PMx accumulation refers to the amount of PMx adsorbed in the unit leaf area at the time the leaves were sampled (µg·cm−2). To determine this, the procedure by Dzierzanowski et al. [4] and Mori et al. [45] was adopted with some modifications. Each leaf sample, taken out of the freezer and brought to room temperature, was washed for 60 s with 250 mL of deionized water under agitation. The washing solution was then first filtered through a metal sieve (Fritsch analysensieb, Idar-Oberstein, Germany) to eliminate particles larger than 100 μm and sequentially filtered using 3 filters in increasing order of retention capacity (type 1288, retention: 10 μm; type 391, retention: 2.5 μm; and PTFE membrane, retention: 0.2 μm), (Sartorius AG, Goettingen, Germany). Filtration was carried out using a filtration apparatus equipped with a 47-mm glass filter funnel (Sartorius stedim, Sartorius AG, Goettingen, Germany) connected to an MV-50 vacuum pump (Comecta-Ivymen, Barcelona, Spain). Immediately before filtration, the PTFE membranes were moistened with a few droplets of isopropyl alcohol to break the surface forces and speed up the process. Prior to filtration, each filter was dried at 60 °C for 30 min in a drying chamber (WTB binder 7200, Tuttlingen, Germany) and then left at a constant air relative humidity (50%) for weight stabilization before being pre-weighed on a high-precision balance (ED224S-OCE, Sartorius, Germany). The main modification to the method of Mori et al. [45] was letting the filters stabilize for 120 min instead of 60 min; the time was selected based on preliminary tests. After filtration the filters were dried again, weight stabilized, and post-weighed. The amount of PM was represented by the difference between the post-weight and pre-weight. At the end of the entire filtration procedure, three fractions of PMx were collected: (1) large (PM10–100), (2) coarse (PM2.5–10), and (3) fine (PM0.2–2.5). These were the most evaluated PM fractions obtained with gravimetric techniques found in the literature, making the results of this study comparable with existing works on this topic. Although ultrafine particles (<0.2 μm) are very dangerous to human health, this fraction was excluded from the present research due to intrinsic methodological limitations. The PM10 fraction was obtained by adding the second and third fractions; the PM2.5 fraction was the same as the third fraction. After washing, the leaf area of each sample was measured using an A3 scanner (HP OfficeJet Pro 7740, HP Development Company, L.P., Palo Alto, CA, USA) and leaf area software (Leaf Area Measurement, version 1.3, University of Sheffield, A.P. Askew, UK). To calculate the area of coniferous leaves, the Leaf Mass per Area (LMA) approach was used. Each needle sample was dried at 70 °C for 72 h (modification of the method in [52]) and then allowed to stabilize for 4 h and weighed. The weight and leaf area of the sub-sample was measured, and the total leaf area of the sample was obtained as a proportion. The amount of PMx accumulation was expressed per unit leaf area (μg·cm−2).

2.5. Determination of PMx Deposition

In this paper, the term PMx deposition refers to the change in accumulation over time (µg·cm−2·day−1). This parameter provides the amount of PM which a plant can capture in a specific time frame. It was calculated for the fractions of PM more dangerous to citizens: PM10 (considered PM10 = PM0.2–2.5 + PM2.5–10) and PM2.5 (considered PM2.5 = PM0.2–2.5). To obtain the deposition, a simplified approach was used. Days without rain were counted from the last effective rainfall (i.e., the one assumed to clean the leaves). In this work, the effective rainfall was considered to be higher than 7 mm day−1 on the basis of the limited existing literature on this topic [35,53,54,55] which, however, highlighted differences depending on the species, PM fraction, and rainfall regimes (intensity and duration). Accumulation was plotted against the number of days without rainfall since the last effective rain event (up to a maximum of 12 days were counted). The deposition rate was calculated as the slope of the time course of accumulation, assuming a linear trend of deposition over the measurement period. Thus, the amount of PM10 and PM2.5 was expressed per unit leaf area and time (μg·cm−2·day−1).

2.6. Statistical Analysis

To evaluate the effect of the species, strata (street or park), species × stratum interaction, leaf position (basal, median, or apical), and season (spring, summer, or fall) within each city, a mixed model analysis was applied to (1) PM10–100, PM2.5–10, and PM0.2–2.5 accumulation per unit leaf area (μg·cm−2) and (2) PM10 and PM2.5 deposition per unit leaf area (μg·cm−2·day−1). The mean values from significant simple factors were separated using Sidak post-hoc tests (p ≤ 0.05). Significant interactions between factors were investigated by one-way ANOVA, and the mean values were separated by Duncan’s post-hoc test (p ≤ 0.05). A Pearson correlation analysis was performed to evaluate the influence of (1) the height of the leaves from the ground on PMx accumulation and (2) the cumulative rainfall, average wind speed, and average PM10 and PM2.5 air concentration (collected 14 days before each sampling day) on PMx accumulation. All statistics were carried out using SPSS software (IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY, USA), while the graphics were drawn with SigmaPlot 12.5 (Systat Software Inc., San Jose, CA, USA).

3. Results

3.1. Meteorological Conditions and Air Quality at Experimental Sites

The meteorological and air quality data measured during the sampling period and in the 2 weeks before at both experimental sites are reported in Table 2.
In Rimini, the rainfall and wind speed were higher during spring compared with summer and fall; the opposite occurred for the air PM concentration. In Krakow, the rainfall was higher in spring and fall than in summer when, on the contrary, the highest wind speed was recorded. The air PM concentration was higher in spring compared with fall and summer.

3.2. PMx Accumulation in Rimini

In Rimini, PM10–100 accumulation was significantly affected by the species, leaf position, and season (Table A1). PM2.5–10 and PM0.2–2.5 accumulation was affected by the species and season and unaffected by the leaf position. The strata never influenced PMx accumulation.
In general, Quercus ilex had a higher PMx accumulation per unit leaf area than other species, regardless of the PM fraction (Figure 2a).
In particular, Quercus ilex accumulated 37% more PM10–100 than Pinus pinea. Ligustrum lucidum, Populus nigra, Prunus laurocerasus, Quercus robur, and Tilia × europaea accumulated, on average, 67% and 47% less PM10–100 than Quercus ilex and Pinus pinea, respectively. Quercus ilex accumulated 55% more PM2.5–10 than Platanus × acerifolia, which showed the lower accumulation among the tested species. Finally, the PM0.2–2.5 accumulation was significantly higher (on average 54%) in Quercus ilex than Aesculus hippocastanum, Ligustrum lucidum, Platanus × acerifolia, and Quercus robur.
The leaf position affected the PM10–100 accumulation, with leaves attached in the lower third of the live canopy height showing a higher accumulation than those attached in the median and distal portions (Figure 2b). This was also confirmed by correlation analysis between the PMx accumulation and the height of the leaves from the ground. At increasing heights from the ground, only the PM10–100 accumulation decreased (data not shown). Conversely, the leaf position did not affect the accumulation of PM2.5–10 and PM0.2–2.5. The basal, median, and apical leaves were in a height range from the ground of 0.20–11.00 m, 1.00–14.20 m, and 1.80–22.00 m, respectively.
The season of sampling affected PMx accumulation. The PM10–100 and PM0.2–2.5 accumulations were higher in fall, followed by summer and spring. The PM2.5–10 accumulation, however, was higher in summer, followed by spring and fall (Figure 2c).

3.3. PMx Accumulation in Krakow

In Krakow, PM10–100 accumulation was affected by the species, stratum, leaf position, and season (Table A1). PM2.5–10 and PM0.2–2.5 were only affected by the species and season, whereas the effects of the stratum and leaf position were not significant. A significant species × stratum interaction was found for PM10–100 and PM2.5–10.
Species with higher accumulations were different depending on the particulate size fraction (Figure 3a). Considering the PM10–100 accumulation, Pinus nigra displayed a higher accumulation than the other species. Tilia cordata ranked second for PM10–100 accumulation. PM10–100 of Acer platanoides and Fraxinus excelsior was, on average, 70% and 32% lower than that in Pinus nigra and Tilia cordata, respectively. Tilia cordata displayed a 20% higher PM2.5–10 accumulation than Sorbus aucuparia and Ulmus laevis. Pinus nigra displayed an intermediate PM2.5–10 capture capacity compared with Tilia cordata, Sorbus aucuparia and Ulmus laevis. Fraxinus excelsior was the lower accumulator of PM2.5–10 among the tested species. PM0.2–2.5 accumulation was significantly higher in Populus nigra compared with Acer platanoides, which was 42% less effective. The other species displayed intermediate performances.
In Krakow, the different species showed different capture capacities depending on the stratum and PM fraction (Figure 3b). Pinus nigra was more efficient in parks compared with streets for the PM10–100 accumulation per unit leaf area. By contrast, Fraxinus excelsior, Quercus robur, and Ulmus laevis showed higher PM10–100 accumulations in the street stratum. For PM2.5–10, the only species with significantly higher values in the street than the park stratum was Populus nigra, and the opposite occurred with Cornus alba. No difference among species depending on the stratum was found in PM0.2–2.5.
The basal leaves accumulated more PM10–100 compared with the median and apical ones (Figure 3c). No differences were found among the leaf positions for other PM fractions. Correlation analysis between the PMx accumulation and the height of the leaves from the ground confirmed that at increasing heights from the ground, the PM10–100 accumulation decreased. In addition, it revealed the same trend for PM2.5–10 (data not shown). The basal, median, and apical leaves were in a height range from the ground of 0.20–16.00 m, 0.55–18.00 m, and 0.80–27.00 m, respectively.
Accumulation was higher in spring compared with other seasons for all PM fractions (Figure 3d). PM10–100 accumulation was higher in fall than in summer, whereas the opposite was found for PM2.5–10. During fall, a lower PM0.2–2.5 accumulation was also observed.

3.4. PMx Deposition in Rimini and Krakow

In Rimini, the species and season significantly affected both PM10 and PM2.5 deposition. In addition, a species × stratum interaction was observed in PM10 (Table A1). Quercus ilex showed significantly higher deposition values for both PM10 and PM2.5 than other species (except Pinus pinea), which were more than two times less efficient (Table 3). Pinus pinea ranked intermediately between Quercus ilex and other species for PMx deposition values. The street trees of Pinus pinea showed a PM10 deposition 1.2 times higher than the park trees of the same species, while the PM2.5 deposition did not differ among the strata within each species (data not shown).
In Krakow, the PM10 and PM2.5 deposition were significantly affected by the species and season, while the strata were only significant for PM10 deposition. Additionally, a significant species × strata interaction was observed for both fractions (Table A1). Tilia cordata displayed almost two times higher PM10 deposition values than Fraxinus excelsior (Table 3). The remaining species showed intermediate deposition capacities.
Pinus nigra showed a significantly higher deposition of PM2.5 compared with Acer platanoides, which was almost two times less efficient, while the other species displayed intermediate deposition rates. Acer platanoides, Aesculus hippocastanum, Quercus robur, and Ulmus laevis trees located in the street stratum showed higher PM10 deposition (about 1.6 times higher on average) than those in the park stratum (data not shown). On the contrary, the park trees of Pinus nigra and Sorbus aucuparia displayed 1.5 and 1.8 times higher deposition values, respectively, compared with the street ones. Aesculus hippocastanum displayed a 2.5 times higher PM2.5 deposition in streets than in parks.

3.5. Comparison among Accumulation and Deposition Trends throughout the Year

The season significantly affected the annual PM10 and PM2.5 accumulation and deposition in both cities. Although the accumulation peaked at different times of the year, depending on the city and PM fraction, an inverse trend between accumulation and deposition was found in both cities for both PM fractions (Figure 4).
The accumulation of PM2.5 increased as the growing season proceeded in Rimini, whereas the trend of PM10 was less clear (Figure 4a,c). Conversely, the deposition of both fractions decreased with leaf aging in Rimini (Figure 4b,d). In Krakow, the accumulation of both PM fractions peaked in spring and then progressively declined as the season progressed (Figure 4e,g), while PM deposition increased (Figure 4f,h).

3.6. Correlation among PMx Leaf Capture and Meteorological and Environmental Parameters

The accumulation of each PM fraction was positively correlated with the accumulation of other PM fractions.
In Rimini, the wind speed and rainfall were negatively correlated with the accumulation for PM10–100 and PM0.2–2.5 but not with the accumulation of PM2.5–10 (Table 4). The PM10 and PM2.5 air concentrations were positively correlated with the accumulation of all PM fractions (except for PM2.5–10, which was not correlated with the PM10 air concentration and slightly negatively correlated with the PM2.5 air concentration).
In Krakow, the wind speed was positively correlated with the accumulation of PM2.5–10 and PM0.2–2.5 but did not correlate with the PM10–100 accumulation. Rainfall, as observed in Rimini, was negatively correlated with the accumulation of all PM fractions. The air PM10 concentration, as observed in Rimini, was positively correlated with all PM accumulation fractions (except for PM0.2–2.5). No correlation was found among the PM accumulation and PM2.5 air concentration.

4. Discussion

4.1. Effect of Species and Strata on PMx Accumulation and Deposition

By providing the results from extensive sampling campaigns conducted in situ on established trees and shrubs, this research corroborated previous findings that species largely differ in their capacity to adsorb atmospheric particulate matter [6,31,32,56]. Larger differences among species were observed for coarser PM fractions compared with finer fractions, reflecting the different aerodynamics properties of the particles and their interactions with different leaf characteristics [30].
Some species displayed high efficiency regardless of particle size, as was the case of Quercus ilex in Rimini. The high accumulation and deposition displayed by this species in all the PM fractions can probably be attributed to the co-occurrence of favorable leaf traits for PM adsorption and retention [57], such as the presence of hairs and trichomes on leaf surfaces, small leaf size, and a thick epicuticular wax layer [5]. Consistently, several authors highlighted that dense leaf hairs, which cover the abaxial side of Quercus ilex leaves, affected the PMx leaf accumulation, increasing the interception surface area and reducing PM re-suspension [4,5,6,34,58,59]. If the PMx accumulation of Quercus ilex is compared to that of Platanus × acerifolia, which also displayed a dense trichome cover in the lower leaf epidermis, our results conform to the idea that the leaf length and width are negatively related to accumulation [30].
Needle-leaved species have been reported to be more effective in PMx accumulation than broadleaves because of their aerodynamic properties, the complex shoot structures, leaf morphology (e.g., the higher surface/volume ratio of needles), and the thicker epicuticular wax layer [4,5,34,39,60,61]. Consistently, in this experiment, Pinus pinea in Rimini and Pinus nigra in Krakow showed higher accumulations and depositions compared with most of the broadleaved species.
Extrinsic factors may also play a role in determining the amount of PM adsorbed on leaves. The accumulations of PM10–100 and PM2.5–10 by Tilia cordata in Krakow (annual average of 6.87 and 3.95 µg·cm−2, respectively) were similar to those previously reported for Tilia cordata in Poland (about 8 and 2.5 µg·cm−2, respectively; see Dzierzanowski et al. [4]) and ranked among the highest observed in this research. This was surprising because its smooth leaf surface, with only small tufts of hair on the abaxial side of the leaf blade, should have made Tilia cordata an inefficient sink for PM [2,5]. A possible explanation for the high amount of particles found in Tilia cordata in this work could be attributable to the honeydew produced by aphids, which was abundant on the foliar surface of the sampled plants and could have increased the trapping efficiency because of its stickiness [25]. Similarly, the high PM0.2–2.5 accumulation observed in Krakow on Populus nigra, another smooth-leaved species with no trichomes, can be explained by the presence of honeydew on the leaf surface, which was also detected in this species. On the other hand, some authors point out that the presence of honeydew may be overestimated by the vacuum filtration method, because honeydew residuals might be weighted together with washed PM [62].
PM accumulation can be also affected by species-specific differences (e.g., leaf traits, canopy shape, and density) within a genus. Sæbø et al. [5] found that Tilia cordata and Tilia × europaea ‘Pallida’ differed for PM accumulation. This may be due to large differences in the leaf properties between the Tilia species. Consistently, high values were observed in Krakow in Tilia cordata, and low or intermediate values were found in Tilia × europaea in Rimini.
By considering the common species investigated in the two cities (Aesculus hippocastanum, Populus nigra, and Quercus robur), the plants in Krakow displayed higher accumulations and depositions than those in Rimini, consistently with higher values of pollution in the city. This underlines that the filter attitude of a species strongly depends on the level of pollution in which it is located [39,61,63].
Different from Rimini, where no differences between street and park particle accumulations were detected, in Krakow, more PMx was captured by plants in the street stratum rather than in park sites, likely because of their proximity to the emission source [64]. An exception was represented by Pinus nigra, which accumulated more PM10–100 in park areas than in the streets. The low tolerance to urban sites of this species made established trees chronically grown in street environments less efficient for air quality amelioration compared with established trees growing in parks. Although having high PMx accumulation capacities, conifers are in general less tolerant to high traffic-related pollution than broadleaves, and they are not recommended for roadside plantings by several authors [5,14,34,65].

4.2. Effect of Leaf Position on PMx Accumulation

Leaves in the lower third of the live crown height showed higher PM10–100 accumulations than those in the upper crown, in agreement with other works [45,46]. Due to their higher size and weight, large particles show a clearer source—sink relationship than coarse and fine ones and settle within a limited vertical distance from the source. This underlines the importance of the barrier density, rather than the barrier height, for the reduction of larger PM fractions and highlights the role of evergreen shrub barriers in air quality improvement along roads [45]. Conversely, finer fractions are easily dispersed in the atmosphere since height does not affect the probability of impact [60]. Dust resuspension caused by human activities like garden maintenance or running in parks [47] and vehicular traffic in streets [45,66] could promote higher accumulations of large PM in the basal leaves, which are close to the ground [67]. Indeed, the concentration of PM in urban environments decreases with increasing height [68]. Moreover, the interception of rainfall by apical leaves and branches decreases the precipitation intensity [66] in the lower crown parts, which results in them being subjected to washing off less. Furthermore, PM intercepted by drops in the apical part of the crown could promote wet deposition on the basal leaves. Above all, these findings support the importance of vegetation at the pedestrian level.

4.3. Effect of the Season on PMx Accumulation and Deposition

The lack of a consistent trend in seasonal accumulation between the two cities denotes that leaf ontogeny alone poorly relates with leaf PM accumulation, unless site-specific environmental factors are considered.
In Rimini, the total PM accumulation (i.e., the sum of all PMx fractions) tended to increase throughout the year, confirming previous findings [38,55]. However, meteorological and environmental conditions can affect the yearly trend of accumulation. In Rimini, the rainfall was higher in spring and then progressively decreased until fall, while the PM10 and PM2.5 air concentrations tended to increase. Heavy rainfall and strong wind, indeed, can remove particles accumulated on the leaf blade [39], and in addition, high levels of pollution can favor PMx accumulation [13,23,25]. In Krakow, where rainfall was evenly distributed through the growing season, the total PM accumulation was higher in spring, when both the air PM10 and PM2.5 concentrations were at their maximum, and then progressively declined until fall.
It is worth noting that the deposition rate was low in leaves displaying high PM accumulations, indicating that if active sites for PM trapping are almost clogged due to a high level of accumulation, less PM deposition can occur. PM is preferentially adsorbed on specific microstructures, such as cuticle ridges, trichomes, grooves, and glands [34]. Thus, although PM often covers a very small fraction of the leaf area [64], the deposition rate decreases as soon as active sites are saturated [69].

4.4. Effect of the Meteorological and Environmental Parameters on PMx Accumulation

The complex dynamics of PM accumulation, wash-off, and re-suspension affect the contribution of vegetation to the air quality. Meteorological and environmental parameters play an important role in this process [55,58,70,71].
As the rain increased, foliar accumulation decreased in both cities as a result of the wash-off effect, making leaves ready for more deposition. However, the effect of precipitation on PM removal depends on the rainfall duration and intensity [54]. After a precipitation event, washed PM reaches the ground. Here, it can be immobilized if the surface is permeable (e.g., open soil or covered with vegetation), or it can be more probably re-suspended in the case of an impermeable surface (e.g., asphalt and other paved surfaces widespread in urban environments) [39]. Considering that most of the urban surfaces are generally sealed, it is important to combine phytoremediation with other techniques (e.g., phytotechnologies such as drainage systems or porous paving) to allow the immobilization of pollutants in urban areas.
Unlike what was observed for the rainfall, the influence of the wind speed on PM capture was opposite in the two cities selected in this work. In Rimini, a coastal town where the wind speed reaches high peaks, wind blew off particles from the foliage, while in Krakow, a continental metropolis where the wind speed is generally lower, it promoted PM accumulation. Indeed, some authors pointed out that strong wind can remove PM from leaves, while weaker wind may enhance the PM load on vegetation [69,72]. However, Sgrigna et al. [67] found that the wind direction influenced particle accumulation more than the wind speed. Consistently, a possible explanation of the positive correlation between wind speed and PM accumulation in Krakow could be the polluted air flow, which moves from coal-fired power stations in the suburbs to the city. For this reason, future experiments should also consider this parameter.
Finally, in this research, PM accumulation on leaves was enhanced by increasing the levels of air PM (with some exceptions). Mitchell et al. [25] observed an increase in leaf PM accumulation until it was in equilibrium with the surrounding air pollution concentration. Thus, the greater the presence of pollutants in the air, the greater the capacity of plants to act as filters.
Above all, it should be considered that meteorological and environmental data were obtained by the representative pollution control units of each city and not by sensors punctually located near each examined plant. For future studies, it will be essential to detect for each sampled plant the microclimatic (rainfall intensity and duration, wind speed and direction, relative humidity, and temperature) and air pollution data as parameters to consolidate and further explore their influence on accumulation dynamics.

5. Conclusions

This research was conducted with extensive in situ measurements on 240 established trees and shrubs belonging to 17 species in 2 cities (Rimini, Italy and Krakow, Poland) used as living laboratories, highlighting the relevance of planning choices for maximizing air filtering by urban forests. It revealed that needle-leaved species (Pinus nigra and Pinus pinea) and broadleaves with small, hairy, and waxy leaves (Quercus ilex) should be preferred, as they displayed the higher potential for air quality amelioration. Extrinsic factors, such as the presence of honeydew, can increase the adsorption of leaves whose functional traits are normally poorly suited for PM removal, such as occurred in this research for Tilia cordata and Populus nigra. A quantitative analysis on the effective surface area for PM retention, including microstructures (e.g., hairs, cuticle ridges, and grooves) and honeydew presence, is required in future studies to address the remaining gaps on this topic.
The trend of PM accumulation throughout the year was inverse among the two cities, indicating that leaf ontogeny alone poorly relates with particle accumulation on leaves, unless site-specific meteorological and environmental factors are considered (e.g., rainfall, wind speed, and air PM concentration). Street trees of some species (e.g., Fraxinus excelsior and Ulmus laevis) were particularly effective at PM capture, but for those species whose health was harmed by growing in a street environment (e.g., Pinus nigra), PM removal declined compared with plants of the same species growing in parks. Careful planning is required to maximize the benefit-to-cost ratio of using vegetation in an urban environment.
A higher accumulation of large PM was found in the lower third of the canopy, underlying the need of trees and shrubs branched from the ground to avoid PM re-suspension and dispersion issues at the pedestrian level, especially along roads affected by vehicular traffic emissions. However, it is worth noting that there may be different design configurations depending on the site characteristics, such as the type of use and available space. In pedestrian spaces or driveways with low planting space, for example, trees with free trunks could be integrated with shrubs branched from the ground to avoid interference with users. This work gives urban planners the possibility to take advantage of many species to design functional arrangements of space for living, answering the air pollution challenge in cities.
Considering the complex and dynamic cycle of PM in urban landscapes, it must be pointed out that this cycle does not end once particles reach plant surfaces. To ensure an effective role of vegetation in air quality improvement, both planning and management measures are needed to definitively remove PM from the environment. At the planning level, it is important to integrate the design of greening with the design of a permeable surrounding environment using, for example, stabilized soils, drainage systems, or porous paving. At the management level, frequent removal of fallen leaves must be favored. How much do planning and management techniques affect the air filtering potential of vegetation in modern cities? Future research could focus on this topic.

Author Contributions

Conceptualization, I.V., D.C. and A.F.; methodology, J.M., I.V., D.C. and A.F.; validation, I.V., D.C. and A.F.; formal analysis, I.V., D.C. and A.F.; investigation, I.V., D.C., J.M., A.F., M.G., S.C., A.P., P.S. and E.C.; resources, I.V., D.C., J.M., A.F., F.F., M.G., A.P., P.S. and E.C.; data curation, I.V., D.C., J.M., M.G. and A.F.; writing—original draft preparation, I.V. and D.C.; writing—review and editing, I.V., D.C., A.F. and F.F.; visualization, I.V. and D.C.; supervision, I.V., D.C., J.M., A.F. and F.F.; project administration, I.V., D.C., J.M., A.F. and F.F.; funding acquisition, A.F. and A.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a LIFE program as a part of the LIFE URBANGREEN project, grant number LIFE 17 CCA/IT/000079.

Acknowledgments

The authors would like to thank UNIMI students Stefano Morina, Giulio Pozzi, Daniele Casati, Pietro Acrami, and Giulia Salvadé, who were involved in the field and laboratory activities, for their valuable work.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table
Table A1. Results of the mixed models for PM10–100, PM2.5–10, and PM0.2–2.5 accumulation (µg·cm−2) and for PM10 and PM2.5 deposition (µg·cm−2·day−1) in Rimini and Krakow.
Table A1. Results of the mixed models for PM10–100, PM2.5–10, and PM0.2–2.5 accumulation (µg·cm−2) and for PM10 and PM2.5 deposition (µg·cm−2·day−1) in Rimini and Krakow.
CityFactorAccumulationDeposition
PM10–100PM2.5–10PM0.2–2.5PM10PM2.5
RiminiSpecies**********
Stratan.s.n.s.n.s.n.s.n.s.
Position**n.s.n.s.n.s.n.s.
Season**********
Species × Stratan.s.n.s.n.s.**n.s.
KrakowSpecies*********
Strata*n.s.n.s.**n.s.
Position**n.s.n.s.n.s.n.s.
Season**********
Species × Strata****n.s.****
* Significant differences at p ≤ 0.05. ** Significant differences at p ≤ 0.01. n.s. = not significant differences.

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Figure 1. Experimental design of measured tree and shrub species in Rimini (a) and Krakow (b).
Figure 1. Experimental design of measured tree and shrub species in Rimini (a) and Krakow (b).
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Figure 2. Effect of species (a), leaf position (b), and season (c) on PM10–100, PM2.5–10, and PM0.2–2.5 accumulation per unit leaf area (µg·cm−2) in Rimini. Within each variable, different letters indicate significant differences among species, leaf positions, or seasons at p ≤ 0.05.
Figure 2. Effect of species (a), leaf position (b), and season (c) on PM10–100, PM2.5–10, and PM0.2–2.5 accumulation per unit leaf area (µg·cm−2) in Rimini. Within each variable, different letters indicate significant differences among species, leaf positions, or seasons at p ≤ 0.05.
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Figure 3. PM10–100, PM2.5–10, and PM0.2–2.5 accumulation per unit leaf area (µg·cm−2) in Krakow by the different species (a) in parks (b1) and streets (b2) with different leaf positions (c) and seasons (d). Within each variable, different letters indicate significant differences among species, species and strata, and leaf positions and seasons at p ≤ 0.05.
Figure 3. PM10–100, PM2.5–10, and PM0.2–2.5 accumulation per unit leaf area (µg·cm−2) in Krakow by the different species (a) in parks (b1) and streets (b2) with different leaf positions (c) and seasons (d). Within each variable, different letters indicate significant differences among species, species and strata, and leaf positions and seasons at p ≤ 0.05.
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Figure 4. PM10 accumulation (a,e) and deposition (b,f) and PM2.5 accumulation (c,g) and deposition (d,h) per unit leaf area in Rimini and Krakow, respectively. Within each variable, different letters indicate significant differences among seasons at p ≤ 0.05. The dotted line represents the annual trend.
Figure 4. PM10 accumulation (a,e) and deposition (b,f) and PM2.5 accumulation (c,g) and deposition (d,h) per unit leaf area in Rimini and Krakow, respectively. Within each variable, different letters indicate significant differences among seasons at p ≤ 0.05. The dotted line represents the annual trend.
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Table
Table 1. Minimum and maximum diameter at breast height (DBH) of measured tree and shrub species in Rimini and Krakow.
Table 1. Minimum and maximum diameter at breast height (DBH) of measured tree and shrub species in Rimini and Krakow.
CitySpeciesDBH Min. (cm)DBH Max. (cm)
RiminiAcer negundo9.8044.56
Aesculus hippocastanum5.5049.34
Ligustrum lucidum8.0030.24
Pinus pinea21.6560.16
Platanus × acerifolia7.6063.66
Populus nigra7.5076.08
Prunus laurocerasus4.0037.88
Quercus ilex11.5059.52
Quercus robur8.3048.38
Tilia × europaea7.0058.89
KrakowAcer platanoides5.0083.40
Aesculus hippocastanum33.00109.18
Cornus alba2.237.00
Fraxinus excelsior4.5081.49
Pinus nigra4.4632.15
Populus nigra18.0090.40
Quercus robur31.0087.54
Sorbus aucuparia5.0029.60
Tilia cordata7.0073.21
Ulmus laevis4.0096.45
Table
Table 2. Mean air temperature, cumulative rainfall, wind speed, relative humidity, and PM10 and PM2.5 air concentration at the experimental sites (Rimini and Krakow) in a period of about 24 days (pre-sampling: 14 days; sampling: 10–11 days).
Table 2. Mean air temperature, cumulative rainfall, wind speed, relative humidity, and PM10 and PM2.5 air concentration at the experimental sites (Rimini and Krakow) in a period of about 24 days (pre-sampling: 14 days; sampling: 10–11 days).
CityPeriodSeasonT (°C)Rain
(mm)		Wind
(m·s−1)		RH
(%)		PM10
(µg·m−3)		PM2.5
(µg·m−3)
Rimini30 April–24 May 2019Spring14.59103.743.1174.3115.604.61
11 June–5 July 2019Summer25.3427.822.4365.3126.0210.13
26 September–19 October 2018Fall15.9325.392.3280.5833.8721.10
Krakow21 May–13 June 2019Spring18.63199.982.5873.1532.4018.22
2–26 July 2019Summer18.35133.212.6565.3326.4014.98
27 August–20 September 2019Fall16.63202.012.4677.5029.7217.45
Table
Table 3. PM10 and PM2.5 deposition (µg·cm−2·day−1) in Rimini and Krakow by the different species.
Table 3. PM10 and PM2.5 deposition (µg·cm−2·day−1) in Rimini and Krakow by the different species.
CitySpeciesPM10 Deposition
(µg·cm−2·day−1)		PM2.5 Deposition
(µg·cm−2·day−1)
RiminiAcer negundo0.879c0.236b
Aesculus hippocastanum0.673c0.150b
Ligustrum lucidum0.706c0.146b
Pinus pinea1.477ab0.335ab
Platanus × acerifolia0.529c0.126b
Populus nigra0.688c0.205b
Prunus laurocerasus0.749c0.195b
Quercus ilex1.932a0.435a
Quercus robur0.976bc0.182b
Tilia × europaea0.759c0.182b
KrakowAcer platanoides1.369bd0.248d
Aesculus hippocastanum1.548ad0.374ad
Cornus alba1.777ac0.405ab
Fraxinus excelsior1.098d0.252cd
Pinus nigra1.978ab0.450a
Populus nigra1.628ac0.398ac
Quercus robur1.620ac0.378ab
Sorbus aucuparia1.321cd0.276cd
Tilia cordata2.062a0.380ad
Ulmus laevis1.642ac0.294bd
Within each variable and city, different letters indicate significant differences among species at p ≤ 0.05.
Table
Table 4. Correlation matrix (Pearson’s coefficient) among leaf PM accumulation (PM10–100, PM2.5–10, and PM0.2–2.5) and mean wind speed, cumulative rainfall, and mean PM10 and PM2.5 air concentrations in Rimini and Krakow. Meteorological and air quality data refer to a period of 14 days before sampling day.
Table 4. Correlation matrix (Pearson’s coefficient) among leaf PM accumulation (PM10–100, PM2.5–10, and PM0.2–2.5) and mean wind speed, cumulative rainfall, and mean PM10 and PM2.5 air concentrations in Rimini and Krakow. Meteorological and air quality data refer to a period of 14 days before sampling day.
CityFactorPM10–100PM2.5–10PM0.2–2.5Wind SpeedRainfallAir PM10Air PM2.5
RiminiPM10–100 0.374 **0.259 **−0.202 **−0.207 **0.222 **0.219 **
PM2.5–10 0.177 ** −0.092 **
PM0.2–2.5 −0.148 **−0.162 **0.162 **0.179 **
Wind speed 0.978 **−0.873 **−0.814 **
Rainfall −0.891 **−0.837 **
Air PM10 0.978 **
Air PM2.5
KrakowPM10–100 0.492 **0.194 ** −0.262 **0.176 **
PM2.5–10 0.411 **0.248 **−0.325 **0.094 *
PM0.2–2.5 0.206 **−0.098 **
Wind speed −0.579 **−0.503 **−0.608 **
Rainfall 0.195 **0.478 **
Air PM10 0.930 **
Air PM2.5
Only significant correlations are shown. * and ** indicate a significant correlation at p ≤ 0.05 and p ≤ 0.01, respectively.
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Vigevani, I.; Corsini, D.; Mori, J.; Pasquinelli, A.; Gibin, M.; Comin, S.; Szwałko, P.; Cagnolati, E.; Ferrini, F.; Fini, A. Particulate Pollution Capture by Seventeen Woody Species Growing in Parks or along Roads in Two European Cities. Sustainability 2022, 14, 1113. https://doi.org/10.3390/su14031113

AMA Style

Vigevani I, Corsini D, Mori J, Pasquinelli A, Gibin M, Comin S, Szwałko P, Cagnolati E, Ferrini F, Fini A. Particulate Pollution Capture by Seventeen Woody Species Growing in Parks or along Roads in Two European Cities. Sustainability. 2022; 14(3):1113. https://doi.org/10.3390/su14031113

Chicago/Turabian Style

Vigevani, Irene, Denise Corsini, Jacopo Mori, Alice Pasquinelli, Marco Gibin, Sebastien Comin, Przemysław Szwałko, Edoardo Cagnolati, Francesco Ferrini, and Alessio Fini. 2022. "Particulate Pollution Capture by Seventeen Woody Species Growing in Parks or along Roads in Two European Cities" Sustainability 14, no. 3: 1113. https://doi.org/10.3390/su14031113

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