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Article

Seasonal Variations in the Particulate Matter Accumulation and Leaf Traits of 24 Plant Species in Urban Green Space

by
Huong-Thi Bui
1,2,†,
Uuriintuya Odsuren
1,†,
Sang-Yong Kim
3 and
Bong-Ju Park
1,2,*
1
Division of Animal, Horticultural, and Food Sciences, Chungbuk National University, Cheongju 28644, Korea
2
Brain Korea 21 Center for Bio-Health Industry, Chungbuk National University, Cheongju 28644, Korea
3
Department of Plant Resources, Korea National Arboretum, Pocheon 11186, Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Land 2022, 11(11), 1981; https://doi.org/10.3390/land11111981
Submission received: 4 October 2022 / Revised: 31 October 2022 / Accepted: 3 November 2022 / Published: 5 November 2022
(This article belongs to the Special Issue Recent Progress in Urban Forest Planning and Monitoring)
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Abstract

:
Particulate matter (PM), an extremely serious type of air pollution, leads to numerous human diseases. Mitigating PM in the urban city, where resident density has been increasing, has been a major challenge. The increase in residents leads to increasing traffic, the primary source of PM in urban areas. Plants play an important role in reducing PM and maintaining an ecological balance. For some Asian countries, such as Korea, with differing seasons and environmental conditions, PM accumulation and plant survival are greatly impacted by environmental conditions. In this study, we analyzed the amount of PM accumulation on the leaf surfaces and wax layers of 24 plant species during four seasons (spring, summer, autumn, and winter) to determine the PM accumulation in plants under different environmental conditions. The leaf traits of plant chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (TChl), relative water content (RWC), leaf extract pH (pH), and leaf specific area (SLA) were analyzed to determine the influence of PM on plants and the relationship between PM and leaf traits. In this study, we found that the amount of PM accumulation differed among plants and seasons. Among the 24 plant species, plants Pinus strobus, P. parviflora, P. densiflora, Euonymus japonicus, and Acer palmatum were most adept at PM accumulation. Leaf structure, environmental conditions, such as PM concentration, and rainfall may be the main factors that impact the ability of plant leaves to accumulate PM. The plant leaf traits differed among the four seasons. PM accumulation on the leaf was negatively correlated with SLA (in all four seasons) and pH (in spring, summer, and autumn). PM was negatively correlated with Chl a, Chl b, and TChl in summer.

1. Introduction

Air pollution has increased over the past 50 years and is considered the world’s largest environmental health problem [1]. Air pollution causes numerous diseases ranging from asthma to cancer, pulmonary illnesses, and heart disease that kill an estimated 7 million people worldwide every year, of which 4.2 million die from stroke, heart disease, lung cancer, and acute and chronic respiratory disease [2]. Particulate matter (PM) is the most dangerous type of air pollution and is a primary concern worldwide, particularly in developing countries. PM with a small diameter that can penetrate the lung alveoli negatively affects the respiratory system [3]. Particulate matter can originate from either anthropogenic or natural sources, such as agriculture or industrial activities, volcanic eruptions, soil erosion, sea salt, or desert sand. According to the aerodynamic diameter, PM can be classified as large PM (>10 μm), coarse (2.5–10 μm), fine (0.1–2.5 μm), and ultrafine (≤0.1 μm), as reported by Sæbø et al. [4].
Plants play a vital role in mitigating urban pollution by accumulating PM on their leaves [5,6,7,8,9]. Plants that grow in urban environments improve air quality and act as a natural filter for PM. In Beijing, China, plants in the city center removed 774 tons of PM10 in one year [10]. However, species differ in their ability to accumulate PM. Plants accumulate PM on their leaf surfaces and epicuticular waxes, so the amount of PM accumulation depends on the macrostructure (plant height, petiole length) and microstructure of the leaf (leaf hairs, thickness wax layer, and stomatal density) [4,11]. Trees with large total leaf areas were considered the most effective type of plants for reducing PM [12]. Other studies have shown that plants growing low to the ground, such as shrubs, can accumulate more PM on the leaf because of exposed soil splash [13]. Several studies have demonstrated that the PM accumulation of needleleaf species is greater than that of broadleaf trees [14,15]. Additionally, the thickness of the wax layer is a factor that can influence the amount of PM accumulated on leaves [16]. Plants with thick wax accumulated more PM than those with thin wax layers. The long petiole length could increase the amount of PM removal from leaves via rain or wind. In addition, the plant’s capacity to capture PM is influenced by several other factors, including environmental variables, such as wind and rain [17]. Wind and rain can wash PM from leaves, decreasing leaf PM accumulation [18]. However, the amount of PM washed from the leaf depends on the leaf structures, density, and area. Plants with a high density of leaves are less influenced by rain [19,20]. Furthermore, the concentration of PM in the atmosphere can directly influence the amount of PM accumulation on the leaf [21]. Under a high PM concentration, plants can accumulate more PM than plants grown in a lower PM concentration environment [22]. However, PM adversely affects plant life [23]. PM impacts plants’ physical and biochemical characteristics [24]. PM influences the structural components of leaves, such as leaf area, leaf thickness, and wax amounts [19,25]. In addition, PM also impacts photosynthesis, leaf extract pH (pH), specific leaf area (SLA), and plant relative water content (RWC) [26]. Popek et al. [27] showed that the effectiveness of photosynthesis was reduced because of PM accumulation on the leaf surface. PM accumulation on the leaf leads to prevention of light absorption or blocking of stomata by reducing the total chlorophyll (TChl) of plants [28]. Therefore, PM also impacts the growth and productivity of plants. However, the impact of PM on plants depends greatly on plant responses [29]. Under different environmental conditions, the ability of PM to accumulate and the influence of PM on individual plant species can differ. The ability of PM accumulation and the tolerance to air pollution are important in selecting suitable plant species for improving urban air quality. However, a few researchers have addressed the correlation between PM accumulation on leaf and leaf traits in common plant species in Korea. Therefore, analyzing PM accumulation on plant leaves and the correlation between PM and leaf trait conditions can inform plant selections designed to improve air quality. Analyzing the complex correlation during different seasons helps to comprehensively determine the correlations among PM, plants, and the environment, which is a premise for selecting plant species to optimize the benefit of the plants in improving air quality in Korea.

2. Materials and Methods

2.1. Study Area and Sample Collection

The study site was located in Chungbuk National University in Cheong-Ju, South Korea, which is located at 36.6290° N, 127.4563° E (Figure 1). Twenty-four plant species that are commonly used for urban greening in Korea were selected for leaf sample collection. Leaf samples were collected from spring 2020 to winter 2021 in four time periods: at the beginning of June (late spring), at the beginning of August (summer), in October (autumn), and in February (late winter). These consisted of 11 evergreen species and 13 deciduous tree species in good condition (healthy and free from disease, insects, and pests) (Table 1). In winter, only the evergreen tree samples were collected because the leaves had fallen from the deciduous trees. For each plant species, we put a tag on the selected plant to ensure that the samples were collected from the same plant. Following each collection, the leaf samples were stored in paper bags and immediately transferred to the laboratory for analysis. The samples were collected after two weeks without heavy rain and between 8 am and 12 noon.

2.2. Leaf Surface PM (sPM) and Epicuticular Wax (wPM) Analysis

According to the method developed by Dzierzanowski et al. [30], leaf samples were washed with distilled water to collect PM on the leaf surface (sPM) and washed with chloroform to collect PM in wax (wPM). Approximately 300 cm2 leaves of each plant species were put in a glass beaker and washed with 250 mL distilled water for 60 s. The glass beaker was placed on an ultrasonic cleaner (WUC-A22H, Daihan Scientific, Wonju, Korea) for 6 min to ensure that all the PM was washed from the leaf surface. Then, the collected solution was passed through a metal sieve (diameter 100 µm mesh) to remove all particles with a diameter over 100 µm. After that, the solution water was filtered with two types of paper filters, type 91 and type 42, with pore sizes of 10 µm and 2.5 µm, respectively. Before filtering, paper filters were placed in a desiccator (DH. DeBG1K, Daihan Scientific, Wonju, Korea) for 48 h to control humidity, and then the filter papers were weighed. Following filtering, the PM was divided into two types: large PM (100–10 µm) and coarse PM (10–2.5 µm). The same method was used to evaluate the weight of the paper filter after filtration. After washing with water, the leaf area was measured by using a leaf area meter (LI-3100C, LI-COR Biosciences, Lincoln, NE, USA). Then, the leaf sample was washed with chloroform and filtered with filter paper by the same filtration methods to determine the amount of wPM. The amount of PM accumulation on the leaves of plants was evaluated using Equation (1):
PM = W2 − W1/A
where W2 is the weight after filtration (g), W1 is the weight before filtration (g), and A is the leaf area (cm2).

2.3. Analysis of Leaf Traits

2.3.1. Chlorophyll (Chl a, Chl b, Total Chlorophyll (Tchl))

The concentration of chlorophyll (Chl a, Chl b, Tchl) was measured according to Lichtenthaler [31]. For each plant species, 0.05 g of fresh weight was placed on the different mortars. Liquid nitrogen was added and crushed. Approximately 10 mL of 100% acetone was added to the mortar, and the sample liquid was collected. A centrifuge (Cef-6, Daihan Scientific, Wonju, Korea) was used to homogenize the samples for 10 m at 4900 rpm. Ten milliliters of supernatant were collected, and the absorbance was analyzed at wavelengths of 470 nm, 616.6 nm, and 644.8 nm by using a spectrophotometer (UV-1800, Shimadzu, Kyoto, Japan). Chl a, Chl b, and TChl were calculated using Equation (2):
Chlorophyll a = (11.24 × A616.6) − (2.04 × A644.8)
Chlorophyll b = (20.13 × A 644.8) − (4.19 × A616.6)
Chlorophyll a + b = (7.05 × A616.6) + (18.09 × A644.8)
where, A616.6, A644.8, and A470 are absorbance values at corresponding wavelengths.

2.3.2. Specific Leaf Area (SLA)

The SLA, which denotes the area per dry mass of the leaf, was measured following Ref. [20]. The leaf area was divided by leaf weight (indirectly indicating leaf thickness) and measured by an LI-3100C (LI-COR Biosciences, Lincoln, NE, USA). Then, the selected leaves were dried using a dry oven (HB-502S, Hanbaek Scientific, Bucheon, Korea) at 70 °C for 48 h to estimate their dry weights. SLA was determined using Equation (3):
SLA (cm−2·g−1) = Leaf area/dry weight

2.3.3. Leaf Extract pH (pH)

The pH was measured using the method developed by Singh et al. [32]. For each plant species, 1.0 g of fresh leaves was placed in a test tube with 10 mL distilled water and homogenized at 2500 rpm for 3 min. Then, the pH value was measured by using a pH meter (HI 8424, Hana Instruments, Woonsocket, RI, USA).

2.3.4. Relative Water Content (RWC)

The RWC was determined according to the method developed by Turner [33]. The leaves were cut to a similar size (5 × 5 cm), and their fresh weight (FW) was immediately measured. After floating them in distilled water at 4 °C for 24 h, their turgid weight (TW) was determined. Finally, they were dried in an oven at 80 °C for 48 h and weighed to measure dry weight (DW). The RWC value was determined using Equation (4):
RWC (%) = [(FW − DW)/(TW − DW)] ×100
where FW = fresh weight, TW = turgid weight, and DW = dry weight.

3. Statistical Analysis

All data were analyzed using SAS software version 9.4 (SAS Institute, Cary, NC, USA) for analysis of variance (ANOVA) with Duncan’s multiple range test (DMRT). The significance level was set at 5%. Variations in the accumulated PM on different plant species and leaf traits in the four seasons were determined using a two-way ANOVA. The relationships between the amount of PM accumulation on the leaf and leaf traits were identified by using Pearson’s correlation analysis. The presented data are given as the means with standard error (±SE).

4. Results and Discussion

4.1. PM Accumulation of Plant Species

In this study, we found that the amount of PM accumulation on leaf surfaces and wax layers differed among various plant species and sampling seasons. The amount of total PM accumulation on leaf surfaces of 24 plant species in the four seasons ranged from 8.32 to 148.43 µg·cm−2 in spring, 7.65 to 137.02 µg·cm−2 in summer, 3.65 to 122.84 µg·cm−2 in autumn, and 21.02 to 264.44 µg·cm−2 in winter (only on the evergreen plants). The amount of total PM accumulation on the wax layer of 24 plant species in spring, summer, autumn, and winter (only on the evergreen plants) ranged from 5.74 to 103.6 µg·cm−2, 4.12 to 116.67 µg·cm−2, 3.81 to 77.22 µg·cm−2, and 17.74 to 236.46 µg·cm−2, respectively. When comparing the amount of PM accumulation on leaves in the four seasons, we found that PM was highest in winter (needleleaf) and spring (broadleaf); conversely, the amount of PM was lowest in autumn. When comparing PM accumulation between needleleaf and broadleaf, the average PM accumulation on leaf surfaces and wax layers was higher on needleleaf than on broadleaf. In spring, the amount of PM accumulation on the leaf surfaces and the wax layers of 10 needleleaf ranged from 148.43 to 14.53 µg·cm−2 and from 103.63 to 16.62 µg·cm−2, respectively. Among the ten needleleaf plants, P. strobus showed the highest PM accumulation, followed by P. parviflora and P. densiflora. In contrast, the amount of PM accumulation in J. chinensis was the lowest. The amount of PM accumulation on the leaf surfaces and the wax layers of 14 broadleaf ranged from 23.75 to 8.32 µg·cm−2 and from 22.89 to 5.74 µg·cm−2, respectively. The plant species that showed the highest PM accumulation on leaf surfaces were A. palmatum followed by E. japonicus and C. chinensis, while G. biloba showed the lowest PM accumulation. The highest PM accumulations on the wax layers were the species E. japonicus, P. × yedoensis, and C. officinalis. Additionally, the plant species with the lowest PM accumulation was V. dilatatum. The amount of PM accumulation in needleleaf was higher than that in all the broadleaf plants except J. chinensis and P. orientalis. In summer, the amount of PM accumulation on the leaf surface and the wax layer of P. strobus was still the highest among needleleaf plants, with PM accumulations of 137.02 and 116.67 µg·cm−2 on the leaf surface and wax layer, respectively. Among the ten needleleaf, P. orientalis showed the lowest PM accumulation on both the leaf surfaces and the wax layer. For broadleaf plants, the amount of PM accumulation on the leaf surfaces ranged from 7.65 to 23.22 µg·cm−2, while the PM accumulation on the wax layer ranged from 4.25 to 13.83 µg·cm−2. Among 13 broadleaf, A. palmatum showed the highest PM accumulation on the leaf surface, and P. × yedoensis showed the highest accumulation on the wax layer. Conversely, G. biloba and R. yedoense showed the lowest PM accumulation on leaf surfaces and wax layers, respectively. In autumn, the amount of PM accumulation on the leaves of 10 needleleaf plants ranged from 8.86 to 122.84 µg·cm−2 on the leaf surfaces and from 8.52 to 77.22 µg·cm−2 on the wax layers, while, in summer, the highest and lowest PM accumulation on both the leaf surfaces and the wax layers were observed for P. strobus and P. orientalis, respectively. These plant species had higher PM accumulation than the other needleleaf plants, followed by P. strobus, P. parviflora, and P. densiflora. For broadleaf, the PM accumulation on the leaf surfaces ranged from 3.65 to 13.62 µg·cm−2 and on the wax layers ranged from 3.81 to 13.39 µg·cm−2. H. syriacus had the highest PM accumulation on the leaf surface, while P. × yedoensis had the highest PM accumulation on the wax layer, followed by E. japonicus and C. officinalis. Conversely, G. biloba and R. yedoense had the lowest PM accumulation on the leaf surface and the wax layer, respectively. In winter, leaf samples of eleven evergreens (ten needleleaf and one broadleaf) were collected. The amount of PM accumulation on the leaf surfaces ranged from 21.02 to 264.44 µg·cm−2 and on the wax layers ranged from 17.74 to 236.46 µg·cm−2. Among the 11 plant species, P. strobus showed the highest PM accumulation on the leaf surface, and T. cuspidata and E. japonicus showed the lowest PM accumulation on the leaf surface and the wax layer, respectively. Among the 24 plant species, P. strobus showed the highest PM accumulation, followed by P. parviflora and P. densiflora. The average PM accumulation on needleleaf was higher than the average PM accumulation on broadleaf by approximately three to over four times. Among broadleaf, A. palmatum and E. japonicus accumulated PM more effectively than other broadleaf (Table 2, Figure 2).
The amount of wax on the leaves of the 24 plant species differed among both plant species and seasons. The amount of wax on the ten needleleaf during four seasons ranged from 81.20 to 755.04 µg·cm−2, 55.95 to 1066.92 µg·cm−2, 51.55 to 910.55 µg·cm−2, and 106.74 to 3793.19 µg·cm−2 in spring, summer, autumn, and winter, respectively. In all the seasons, the amount of wax on P. strobus was the highest, followed by P. densiflora, while T. cuspidata showed the lowest amount of wax among the ten needleleaf. The wax on 13 broadleaf ranged from 15.68 to 95.41 µg·cm−2, 15.76 to 191.50 µg·cm−2, and 14.91 to 149.12 µg·cm−2 in spring, summer, and autumn, respectively. The amount of wax on E. japonicus was highest in spring, and the amount of wax on V. dilatatum was highest in summer and autumn. In winter, the amount of wax on E. japonicus was 160.86 µg·cm−2. When comparing the amount of wax on needleleaf and broadleaf, we found that the amount of wax on all the needleleaf plants in spring, autumn, and summer was higher than that on broadleaf except for T. cuspidata. Among the 24 plant species, the amount of wax on P. strobus was higher than that of the other plant species (Figure 3).
Total sPM: (sPM (10–100 µm) + sPM2.5 (2.5–10 µm)), total wPM: (wPM (10–100 µm) + wPM2.5 (2.5–10 µm)).
Plant accumulation of PM occurs directly on leaves, so the leaf structure contributes to the ability of plants to accumulate PM. In this study, we found that the amount of PM accumulation on the leaves of 24 plant species was different among plant species and the four seasons. The amount of PM accumulation on the leaves of plants depends on leaf structures and environmental conditions [34]. The increasing PM concentration in the environment could lead to an increase in the amount of PM accumulation on the leaves of plants [35]. In this study, the PM concentration level was highest in winter, which could cause the highest PM accumulation on the needleleaf [36]. For the broadleaf, the PM accumulation on the leaf surface was higher in spring than in the other seasons due to the PM concentration in this season being higher than in summer and autumn. Under different environments, the PM concentration level, rainfall, and wind impact the amount of PM accumulation on leaves [37,38]. The high rainfall in summer and autumn could wash PM from a leaf, causing decreasing PM accumulation on the leaves of plants in the two seasons. The amount of PM accumulation in the 24 plant species tended to be higher in needleleaf than in broadleaf. Numerous studies have also shown that needleleaf are more effective in PM accumulation than broadleaf because of their high stomatal concentration and large amount of leaf wax [39,40]. The needleleaf secrete mucus oils on their leaf surfaces, reducing the amount of PM washed from leaves [41]. The trees, with their large leaf area, were considered the most effective PM accumulation plants. Although the crowns of the shrubs were much lower than the trees, nearing the ground helped shrubs accumulate PM closer to the ground [4]. In this study, the shrubs E. japonicus and R. yedoense showed more effective PM accumulation on the leaf surface than others.
Among the ten needleleaf, P. strobus showed the highest PM accumulation on the leaf surface. The high stomatal concentration on the leaf could increase the PM accumulation on the leaf of P. strobus. Additionally, the amount of wax on P. strobus was the highest, causing an increasingly large amount of PM accumulation in this plant species. Other studies also showed that P. parviflora and P. densiflora were able to accumulate more PM than other plant species, which was the same as our result. Among the 14 broadleaf, the plant species that showed the most effective PM accumulation were A. palmatum and E. japonicus because of their leaf structures. Leaf structures, such as heave, groove, vein, chambers, bumps, glands, and secretions, impact PM deposition on leaves [42]. Many studies have shown that plants with rough leaves can accumulate more PM than plants with smooth leaves [39]. However, E. japonicus with smooth leaves showed high effective accumulation on leaves because of the plant’s curled leaf edges, which could keep PM on the leaf apices despite the washing effect of rainfall. Moreover, the glands and secretions of the leaves were related to increasing PM accumulation in E. japonicus. For A. palmatum, the leaf fold structure led to increased PM accumulation. Conversely, G. biloba, with a rough leaf and high leaf area, showed the lowest PM accumulation. The long leaf petiole increased the wind’s effective removal of PM from its leaves [43]. The ridged microstructure and dense wax tubules, due to the high self-cleaning ability of G. biloba, reduced the effective accumulation of PM in G. bibola [44]. The water repellency of the leaf prevented PM deposition on the leaf, which was also one of the reasons that led to decreasing PM accumulation on the leaf of G. bibola. The amount of wax on 24 plants differed due to their structural differences. The amount of wax in winter increased in response to the increasing PM in the atmosphere. The PM concentration level is positively correlated with the amount of wax in plants [45]. Leaf structures impacted the ability of PM to accumulate in the plants. However, other factors, such as leaf shape, canopy shape, and leaf height, need to be studied to better understand the complex relationships of plant species and PM accumulation.

4.2. The Leaf Traits of 24 Plant Species

In this study, the leaf traits of 24 plant species were analyzed. Among the leaf traits, the Chl a, Chl b, TChl, carotenoid, and RWC were different among plant species and seasons. We did not find any seasonal tendencies when comparing the Chl a and carotenoid contents of the 24 plant species. For the Chl b of 24 plant species, we found that Chl b tended to be lower in autumn than in summer; the species not following this trend were P. strobus, Z. serrata, and L. obtusifolium. The TChl of 24 plant species showed the same tendency as the Chl b, but T. cuspidata, A. holophylla, P. strobus, Z. serrata, and L. obtusifolium did not follow this trend. The RWC of the 24 plant species differed among the plants. In this study, the RWC of broadleaf did not show any seasonal tendencies. However, the RWC of needleleaf increased in autumn compared with summer. When comparing the RWC of needleleaf between autumn and winter, the RWC decreased in winter except in P. strobus. The pH differed among plant species. We found that the pH increased in autumn compared with summer for all plant species except J. chinensis and P. parviflora. The pH of 11 plant species was higher in winter than in other seasons. Additionally, the SLA of 24 plants differed among plant species. Among the four seasons, we found that the SLA of 11 plant species, except for A. holophylla and P. strobus, was lowest in winter. When comparing the SLA among the three seasons (spring, summer, and autumn), we did not find any seasonal tendencies (Table 3 and Table 4).
PM impacts plant growth and production by impacting its physiology and biological activities. Under stress from the environment, numerous changes in plants can be observed. However, the level of change depends on the response of the plants to the environment [26]. In this study, the leaf traits (chlorophyll, pH, RWC, and SLA) were analyzed to determine the influence of PM on the plant while the plant responded to environmental stress. Chlorophyll content signifies the photosynthesis process that determines plant growth and production [46]. PM accumulation on the leaf could block the stomata, leading to reduced stomatal conductance, which leads to reduced chlorophyll content in the plants [17]. Moreover, PM accumulation on the leaf prevented light absorption due to the decreasing effectiveness of photosynthesis [47]. PM could even lead to chlorosis (yellowing) in plants. In this study, the decreasing chlorophyll content of broadleaf caused them to change from green to yellow at the end of the growing season. We did not find any patterns among the chlorophyll content of the plants, but we suggest that the chlorophyll reduction in some plants caused PM to accumulate on the leaves. The increase in the chlorophyll content of other plants during the high PM concentration season showed plant tolerance to environmental stress [48]. In this study, we also found that the large sPM (10–100 µm), wPM (10–100 µm), and coarse wPM (2.5–10 µm) showed negative correlations with plant chlorophyll and carotenoid in summer, but, in winter, we found positive correlations between coarse wPM (2.5–10) and chlorophyll and carotenoid. In winter, the needleleaf and one broadleaf (E. japonica) were collected and analyzed.
The RWC reflected the status of water of plants, which plays a significant role in maintaining plant physiological balance. Plants with a high RWC could be more tolerant to stress from the environment, such as drought or air pollution [49]. PM locked on stomata led to a decreasing transpiration rate, which decreased the water pulled from plant roots and was a reason why minerals could not translate from plant roots for biosynthesis [6]. In this study, we suggested that the increase in PM concentration in winter caused a decrease in the RWC of needleleaf. In contrast, the increasing RWC of a plant in the high PM concentration season showed the high tolerance level of the plants to air pollution.
Further, pH is a sensitive indicator of stress in plant environments. Moreover, low pH reduces conversion of hexose sugar to ascorbic acid, which plays an important role in the tolerance level of plants [30]. Therefore, plants with a high pH have a greater ability to tolerate air pollution than plants with a low pH. Air pollutants lead to decreasing pH, which causes sensitive stomata due to reduced plant photosynthesis rates. Furthermore, acidic pollution, such as SO2 and NO2, is one reason for the decreasing pH of plants [50]. In this study, the increasing pH of needleleaf (in winter) and broadleaf (in autumn) may have caused the plants to respond to air pollution. We found a negative correlation between PM accumulation on leaves and pH in spring, summer, and autumn. Other factors, such as environmental soil pH, that could impact plant pH need to be studied to determine the correlation between pH and these factors.
SLA measures the thickness of the leaf. The changes in SLA mirror the changes in leaf structure and nutritional content. The thickness of leaves can help to increase effective light absorption [33]. However, PM accumulation on the leaf surface may increase the leaf’s shape area and cause changes in the SLA of plants. Based on plant protective or adaptive mechanisms, SLA fluctuation levels vary [51]. In this study, we found that the SLA of the plant was different among species. Moreover, the SLA of needleleaf was lowest in winter, which caused a large amount of PM accumulation on the leaf surface of needleleaf during this season. We also found that PM accumulation was negatively correlated with plant SLA (Table 5).

5. Conclusions

In this study, we found that the amount of PM accumulation on the leaves of 24 plant species differed among the four seasons. In winter, the amount of PM accumulation increased with increasing PM concentration in the atmosphere. In summer and autumn, the low PM concentration and the high rainfall may have led to a reduction in the amount of PM accumulation on the plant leaves. In this study, needleleaf was more effective than broadleaf in accumulating PM. The shrubs demonstrated to be highly effective at reducing PM. Using both trees and shrubs can increase the effective PM accumulation in the urban area. The P. strobus, P. parviflora, P. densiflora, E. japonicus, and A. palmatum showed more effective PM accumulation than other plant species. The leaf traits differed regarding plant species and seasons. PM had a negative correlation with plant SLA. In summer, PM was negatively correlated with chlorophyll and carotenoids. Further, pH had a negative correlation with PM accumulation on the leaves in spring, summer, and autumn. PM accumulation impacted the leaf traits of the plant, but numerous other factors, such as temperature and soil, also impact leaf traits. More studies on the complex correlations among leaf PM accumulation, leaf traits, and environmental conditions are needed to effectively increase the use of plants to improve air quality.

Author Contributions

Conceptualization, S.-Y.K. and B.-J.P.; methodology, S.-Y.K. and B.-J.P.; investigation, H.-T.B. and U.O.; data analysis, H.-T.B. and U.O.; writing—review and editing, S.-Y.K. and B.-J.P.; funding acquisition B.-J.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the support of the R&D program for Forest Science Technology (Project No. 2019155B10-2021-001) provided by Korea Forest Service (Korea Forestry Promotion Institute), and this work was conducted during the research year of Chungbuk National University in 2021.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data supporting the conclusions of this article are included in this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Doreswamy; Harishkumar, K.S.; Yogesh, K.M.; Ibrahim, G. Forecasting air pollution particulate matter (PM2.5) using machine learning regression models. Procedia Comput. Sci. 2020, 171, 2057–2066. [Google Scholar] [CrossRef]
  2. WHO. WHO’s global air-quality guidelines. Lancet 2006, 368, 1302. [Google Scholar] [CrossRef]
  3. Mukherjee, A.; Agrawal, M. World air particulate matter: Sources, distribution and health effects. Environ. Chem. Lett. 2017, 15, 283–309. [Google Scholar] [CrossRef]
  4. Sæbø, A.; Popek, R.; Nawrot, B.; Hanslin, H.M.; Gawronska, H.; Gawronski, S.W. Plant species differences in particulate matter accumulation on leaf surfaces. Sci. Total Environ. 2012, 427–428, 347–354. [Google Scholar] [CrossRef]
  5. Kwon, K.-J.; Urrintuya, O.; Kim, S.-Y.; Yang, J.-C.; Sung, J.-W.; Park, B.-J. Removal potential of particulate matter of 12 woody plant species for landscape planting. J. People Plants Environ. 2020, 23, 647–654. [Google Scholar] [CrossRef]
  6. Bui, H.-T.; Ousuren, U.; Kwon, K.-J.; Kim, S.-Y.; Yang, J.-C.; Jeong, N.-R.; Park, B.-J. Assessment of air pollution tolerance and particulate matter accumulation of 11 woody plant species. Atmosphere 2021, 12, 1067. [Google Scholar] [CrossRef]
  7. Bui, H.-T.; Odsuren, U.; Jeong, M.; Seo, J.-W.; Kim, S.-Y.; Park, B.-J. Evaluation of the air pollution tolerance index of 12 plant species growing in environments with different air pollution levels. J. People Plants Environ. 2022, 25, 23–31. [Google Scholar] [CrossRef]
  8. Bui, H.-T.; Odsuren, U.; Kim, S.-Y.; Park, B.-J. Particulate matter accumulation and leaf traits of ten woody species growing with different air pollution conditions in Cheongju City, South Korea. Atmosphere 2022, 13, 1351. [Google Scholar] [CrossRef]
  9. Wróblewska, K.; Jeong, B.R. Effectiveness of plants and green infrastructure utilization in ambient particulate matter removal. Envrion. Sci. Eur. 2021, 33, 110. [Google Scholar] [CrossRef]
  10. Zhang, W.K.; Wang, B.; Niu, X. Study on the adsorption capacities for airborne particulates of landscape plant in different polluted regions in Beijing (China). Int. J. Envrion. Res. Public Health 2015, 12, 9623–9638. [Google Scholar] [CrossRef]
  11. Zhang, W.; Wang, B.; Niu, X. Relationship between leaf surface characteristics and particle capturing capacities of different tree species in Beijing. Forests 2017, 8, 92. [Google Scholar] [CrossRef] [Green Version]
  12. McDonald, A.G.; Bealey, W.J.; Fowler, D.; Dragosits, U.; Skiba, U.; Smith, R.I.; Donovan, R.G.; Brett, H.E.; Hewitt, C.N.; Nemitz, E. Quantifying the effect of urban tree planting on concentrations and depositions of PM10 in two UK conurbations. Atmos. Environ. 2007, 41, 8455–8467. [Google Scholar] [CrossRef]
  13. Mo, L.; Ma, Z.; Xu, Y.; Sun, F.; Lun, X.; Liu, X.; Chen, J.; Yu, X. Assessing the capacity of plant species to accumulate particulate matter in Beijing, China. PLoS ONE 2015, 10, e0140664. [Google Scholar] [CrossRef] [PubMed]
  14. Popek, R.; Gawrońska, H.; Wrochna, M.; Gawroński, S.W.; Sæbø, A. Particulate matter on foliage of 13 woody species: Deposition on surfaces and phytostabilisation in waxes—A 3-year study. Int. J. Phytoremediation 2013, 15, 245–256. [Google Scholar] [CrossRef] [PubMed]
  15. Zhang, W.; Zhang, Z.; Meng, H.; Zhang, T. How does leaf surface micromorphology of different trees impact their ability to capture particulate matter? Forests 2018, 9, 681. [Google Scholar] [CrossRef] [Green Version]
  16. Leonard, R.J.; McArthur, C.; Hochuli, D.F. Particulate matter deposition on roadside plants and the importance of leaf trait combination. Urban For. Urban Green. 2016, 20, 249–253. [Google Scholar] [CrossRef]
  17. Przybysz, A.; Popek, R.; Gawrońska, H.; Grab, K.; Łoskot, K.; Wrochna, M.; Gawroński, S.W. Efficiency of photosynthetic apparatus of plants grown in sites differing in level of particulate matter. Acta Sci. Pol. Hortorum Cultus 2014, 13, 17–30. [Google Scholar]
  18. Wang, H.; Shi, H.; Wang, Y. Effects of weather, time, and pollution level on the amount of particulate matter deposited on leaves of Ligustrum lucidum. Sci. World J. 2015, 2015, 935942. [Google Scholar] [CrossRef] [Green Version]
  19. Chen, L.; Liu, C.; Zhang, L.; Zou, R.; Zhang, Z. Variation in tree species ability to capture and retain airborne fine particulate matter (PM2.5). Sci. Rep. 2017, 7, 3206. [Google Scholar] [CrossRef] [Green Version]
  20. Popek, R.; Haynes, A.; Przybysz, A.; Robinson, S.A. How much does weather matter? Effects of rain and wind on PM accumulation by four species of Australian native trees. Atmosphere 2019, 10, 633. [Google Scholar] [CrossRef] [Green Version]
  21. Chaturvedi, R.K.; Prasad, S.; Pana, S.; Obaidullah, S.M.; Pandey, V.; Singh, H. Effects of dust load on the leaf attributes of the tree species growing along the roadside. Environ. Monit. Assess. 2013, 185, 383–391. [Google Scholar] [CrossRef] [PubMed]
  22. Kong, K.; Yu, H.; Chen, M.; Piao, Z.; Dang, J.; Sui, Y. Effects of particle matters on plant: A review. Phyton 2019, 88, 367–378. [Google Scholar] [CrossRef] [Green Version]
  23. Farmer, A.M. The effects of dust on vegetation—A review. Environ. Pollut. 1993, 79, 63–75. [Google Scholar] [CrossRef]
  24. Mulenga, C.; Clarke, C.; Meincken, M. Physiological and growth responses to pollutant-induced biochemical changes in plants: A review. Pollution, Pollution 2020, 6, 827–848. [Google Scholar] [CrossRef]
  25. He, C.; Qie, K.; Pott, R. Reduction of urban traffic-related particulate matter-leaf trait matters. Environ. Sci. Pollut. Res. 2020, 27, 5825–5844. [Google Scholar] [CrossRef] [PubMed]
  26. Panda, L.R.L.; Aggarwal, R.K.; Bhardwaj, D.R. A review on air pollution tolerance index (APTI) and anticipated performance index (API). Curr. World Environ. 2018, 13, 55–65. [Google Scholar] [CrossRef] [Green Version]
  27. Popek, R.; Przybysz, A.; Gawrońska, H.; Klamkowski, K.; Gawroński, S.W. Impact of particulate matter accumulation on the photosynthetic apparatus of roadside woody plants growing in the urban conditions. Ecotoxicol. Environ. Saf. 2018, 163, 56–62. [Google Scholar] [CrossRef]
  28. Shannigrahi, A.S.; Fukushima, T.; Sharma, R.C. Anticipated air pollution tolerance of some plant species considered for green belt development in and around an industrial/urban area in India: An overview. Int. J. Environ. Stud. 2004, 61, 125–137. [Google Scholar] [CrossRef]
  29. Ter, S.; Chettri, M.K.; Shakya, K. Air pollution tolerance index of some tree species of Pashupati and Budhanilkantha area, Kathmandu. Amrit Res. J. 2020, 1, 20–28. [Google Scholar] [CrossRef]
  30. Dzierzanowski, K.; Popek, R.; Gawrońska, H.; Saebø, A.; Gawroński, S.W. Deposition of particulate matter of different size fractions on leaf surfaces and in waxes of urban forest species. Int. J. Phytoremediation 2011, 13, 1037–1046. [Google Scholar] [CrossRef]
  31. Lichtenthaler, H.K. Chlorophylls and carotenoids: Pigments of photosynthetic biomembranes. In Methods in Enzymology; Elsevier: Amsterdam, The Netherlands, 1987; Volume 148, pp. 350–382. [Google Scholar]
  32. Singh, S.; Rao, D.; Agrawal, M.; Pandey, J.; Naryan, D. Air pollution tolerance index of plants. J. Environ. Manag. 1991, 32, 45–55. [Google Scholar] [CrossRef]
  33. Turner, N.C. Techniques and experimental approaches for the measurement of plant water status. Plant Soil 1981, 58, 339–366. [Google Scholar] [CrossRef]
  34. Xu, X.; Yu, X.; Mo, L.; Xu, Y.; Bao, L.; Lun, X. Atmospheric particulate matter accumulation on trees: A comparison of boles, branches and leaves. J. Clean. Prod. 2019, 226, 349–356. [Google Scholar] [CrossRef]
  35. Ahmad, I.; Abdullah, B.; Dole, J.M.; Shahid, M.; Ziaf, K. Evaluation of the air pollution tolerance index of ornamentals growing in an industrial area compared to a less polluted area. Hortic. Environ. Biotechnol. 2019, 60, 595–602. [Google Scholar] [CrossRef]
  36. He, C.; Qiu, K.; Alahnad, A.; Pott, R. Particulate matter capturing capacity of roadside evergreen vegetation during the winter season. Urban For. Urban Green. 2020, 48, 126510. [Google Scholar] [CrossRef]
  37. Beckett, K.P.; Freer-Smith, P.H.; Taylor, G. Particulate pollution capture by urban trees: Effect of species and windspeed. Glob. Chang. Biol. 2000, 8, 995–1003. [Google Scholar] [CrossRef]
  38. Xu, X.; Zhang, Z.; Bao, L.; Mo, L.; Yu, X.; Fan, D.; Lun, X. Influence of rainfall duration and intensity on particulate matter removal from plant leaves. Sci. Total Environ. 2017, 609, 11–16. [Google Scholar] [CrossRef]
  39. Jin, E.J.; Yoon, J.H.; Bae, E.J.; Jeong, B.R.; Yong, S.H.; Choi, M.S. Particulate matter removal ability of ten evergreen trees planted in Korea urban greening. Forests 2021, 12, 438. [Google Scholar] [CrossRef]
  40. Li, Y.; Wang, S.; Chen, Q. Potential of thirteen urban greening plants to capture particulate matter on leaf surfaces across three levels of ambient atmospheric pollution. Int. J. Environ. Res. Public Health 2019, 16, 402. [Google Scholar] [CrossRef] [Green Version]
  41. Liu, J.; Cao, Z.; Zou, S.; Liu, H.; Hai, X.; Wang, S.; Duan, J.; Xi, B.; Yan, G.; Zhang, S.; et al. An investigation of the leaf retention capacity, efficiency and mechanism for atmospheric particulate matter of five greening tree species in Beijing, China. Sci. Total Environ. 2018, 616–617, 417–426. [Google Scholar] [CrossRef]
  42. Shi, J.; Zhang, G.; An, H.; Yin, W.; Xia, X. Quantifying the particulate matter accumulation on leaf surfaces of urban plants in Beijing, China. Atmos. Pollut. Res. 2017, 8, 836–842. [Google Scholar] [CrossRef]
  43. Han, D.; Shen, H.; Duan, W.; Chen, L. A review on particulate matter removal capacity by urban forests at different scales. Urban For. Urban Green. 2020, 48, 126565. [Google Scholar] [CrossRef]
  44. Chen, G.; Lin, L.; Zhang, Y.; Ma, K. Net particulate matter removal ability and efficiency of ten plant species in Beijing. Urban For. Urban Green. 2021, 63, 127230. [Google Scholar] [CrossRef]
  45. Popek, R.; Łukowsk, A.; Karolewski, P. Particulate matter accumulation—Further differences between native Prunus padus and non-native P. serotina. Dendrobiology 2017, 78, 85–95. [Google Scholar] [CrossRef] [Green Version]
  46. Tripathi, A.K.; Gautnam, M. Biochemical parameters of plants as indicators of air pollution. J. Environ. Biol. 2007, 28, 127–132. [Google Scholar] [PubMed]
  47. Popek, R.; Łukowski, A.; Grabowski, M. Influence of particulate matter accumulation on photosynthetic apparatus of Physocarpus opulifolius and Sorbaria sorbifolia. Pol. J. Environ. Stud. 2018, 27, 2391–2396. [Google Scholar] [CrossRef]
  48. Giri, S.; Shrivastava, D.; Deshmukh, K.; Dubey, P. Effect of air pollution on chlorophyll content of leaves. Curr. Agric. Res. J. 2013, 1, 93–98. [Google Scholar] [CrossRef]
  49. Ghafari, S.; Kaviani, B.; Sedaghathoor, S.; Allahyari, M.S. Assessment of air pollution tolerance index (APTI) for some ornamental woody species in green space of humid temperature region (Rasht, Iran). Environ. Dev. Sustain. 2020, 23, 1579–1600. [Google Scholar] [CrossRef]
  50. Rai, P.K.; Panda, L.L.S.; Chutia, B.M.; Singh, M.M. Comparative assessment of air pollution tolerance index (APTI) in the industrial (Rourkela) and non industrial area (Aizawl) of India: An ecomanagement approach. Afr. J. Environ. Sci. Technol. 2013, 7, 944–948. [Google Scholar] [CrossRef]
  51. Wuytack, T.; Wuyts, K.; Van Dongen, S.; Baeten, L.; Kardel, F.; Verheyen, K.; Samson, R. The effect of air pollution and other environmental stressors on leaf fluctuating asymmetry and specific leaf area of Salix ablba L. Environ. Pollut. 2011, 159, 2405–2411. [Google Scholar] [CrossRef]
Land 11 01981 g001 550
Figure 1. The location map of the sampling sites. Chungbuk National University, Cheongju City, Korea.
Figure 1. The location map of the sampling sites. Chungbuk National University, Cheongju City, Korea.
Land 11 01981 g001
Land 11 01981 g002 550
Figure 2. The amount of PM accumulation on the leaf surface and wax of 24 plant species. (A): Spring, (B): summer, (C): autumn, (D): winter.
Figure 2. The amount of PM accumulation on the leaf surface and wax of 24 plant species. (A): Spring, (B): summer, (C): autumn, (D): winter.
Land 11 01981 g002
Land 11 01981 g003 550
Figure 3. The amount of wax on 24 plant species in four seasons (spring, summer, autumn, and winter).
Figure 3. The amount of wax on 24 plant species in four seasons (spring, summer, autumn, and winter).
Land 11 01981 g003
Table
Table 1. List of landscaping plants analyzed in this study.
Table 1. List of landscaping plants analyzed in this study.
SpeciesFamilyHabitType
Juniperus chinensis L.CupressaceaeTreeEvergreen
Juniperus chinensis var. kaizuka Hort.CupressaceaeTreeEvergreen
Pinus parviflora Siebold & Zucc.PinaceaeTreeEvergreen
Pinus densiflora Siebold & Zucc.PinaceaeTreeEvergreen
Chamaecyparis pisifera Siebold & Zucc.CupressaceaeTreeEvergreen
Taxus cuspidata Siebold & Zucc.TaxaceaeTreeEvergreen
Abies holophylla Maxim.PinaceaeTreeEvergreen
Picea abies (L.) H.Karst.PinaceaeTreeEvergreen
Pinus strobus L.PinaceaeTreeEvergreen
Platycladus orientalis (L.) FrancoCupressaceaeTreeEvergreen
Euonymus japonica Thunb.CelastraceaeShrubEvergreen
Magnolia denudata Desr.MagnoliaceaeTreeDeciduous
Aesculus turbinata BlumeHippocastanaceaeTreeDeciduous
Rhododendron yedoense MaximEricaceaeShrubDeciduous
Hibiscus syriacus L.MalvaceaeShrubDeciduous
Acer palmatum Thunb.AceraceaeTreeDeciduous
Cercis chinensis BungeFabaceaeShrubDeciduous
Cornus officinalis Siebold&Zucc.CornaceaeTreeDeciduous
Acer triflorum Kom.AceraceaeTreeDeciduous
Zelkova serrata (Thunb.) MakinoUlmaceaeTreeDeciduous
Ginkgo biloba L.GinkgoaceaeTreeDeciduous
Ligustrum obtusifolium Siebold & Zucc.OleaceaeShrubDeciduous
Prunus x yedoensis Matsum.RosaceaeTreeDeciduous
Viburnum dilatatum Thunb.AdoxaceaeShrubDeciduous
Table
Table 2. The total PM accumulation on the leaf surface and the wax layer of 24 plant species in four seasons (spring, summer, autumn, and winter).
Table 2. The total PM accumulation on the leaf surface and the wax layer of 24 plant species in four seasons (spring, summer, autumn, and winter).
SpeciesTotal sPM (µg·cm−2)Total wPM (µg·cm−2)
SpringSummerAutumnWinterSpringSummerAutumnWinter
J. chinensis14.5 ± 4.112.5 ± 2.112.6 ± 1.726.5 ± 1.116.6 ± 0.913.6 ± 3.412.2 ± 4.730.3 ± 1.2
J. chinensis var. kaizuka26.5 ± 1.612.8 ± 1.110.9 ± 1.531.3 ± 0.228.7 ± 1.813.3 ± 2.819.4 ± 6.838.1 ± 1.3
P. parviflora113.9 ± 26.465.6 ± 7.154.1 ± 11.8138.8 ± 7.540.4 ± 7.529.3 ± 6.656.8 ± 8.771.8 ± 8.4
P. densiflora72.9 ± 2.775.1 ± 11.456.8 ± 6.072.7 ± 6.852.1 ± 5.647.8 ± 1.751.0 ± 10.281.3 ± 3.2
C. pisifera24.8 ± 2.731.1 ± 7.511.5 ± 0.631.5 ± 0.923.5 ± 1.311.3 ± 0.616.5 ± 9.524.8 ± 3.2
T. cuspidata25.7 ± 4.540.1 ± 5.09.0 ± 0.521.0 ± 0.724.3 ± 2.312.8 ± 1.310.4 ± 0.220.7 ± 0.5
A. holophylla43.8 ± 3.617.5 ± 3.415.5 ± 0.367.5 ± 10.834.7 ± 11.135.3 ± 3.816.6 ± 2.546.0 ± 3.4
P. abies30.7 ± 1.220.1 ± 0.522.7 ± 2.255.8 ± 4.928.4 ± 4.320.8 ± 0.723.3 ± 1.832.7 ± 3.3
P. strobus148.4 ± 23.0137.0 ± 31.8122.8 ± 25.8264.4 ± 31.1103.6 ± 22.2116.7 ± 5.477.2 ± 27.5236.5 ± 23.1
P. orientalis22.0 ± 2.311.6 ± 1.18.9 ± 0.928.7 ± 2.125.3 ± 1.39.3 ± 1.48.5 ± 0.828.8 ± 1.7
E. japonicus23.7 ± 3.417.9 ± 0.312.9 ± 1.027.7 ± 3.222.9 ± 5.28.7 ± 0.510.7 ± 1.417.7 ± 1.6
M. denudata10.9 ± 1.011.5 ± 0.89.0 ± 0.4-9.8 ± 0.76.7 ± 0.46.2 ± 0.8-
A. turbinata12.9 ± 0.89.9 ± 0.76.8 ± 1.1-9.2 ± 1.09.0 ± 0.54.5 ± 0.5-
R. yedoense16.0 ± 2.39.8 ± 0.29.8 ± 0.7-11.0 ± 0.24.1 ± 0.93.8 ± 0.7-
H. syriacus16.9 ± 0.416.6 ± 1.213.6 ± 1.9-12.0 ± 0.16.0 ± 0.36.3 ± 1.9-
A. palmatum23.8 ± 2.423.2 ± 9.912.6 ± 0.7-9.2 ± 0.66.6 ± 1.38.1 ± 1.3-
C. chinensis17.6 ± 2.110.8 ± 0.04.8 ± 0.7-10.3 ± 0.65.1 ± 0.17.3 ± 2.2-
C. officinalis16.2 ± 0.617.6 ± 0.912.7 ± 0.4-15.8 ± 1.35.2 ± 0.412.2 ± 1.2-
A. triflorum15.3 ± 0.813.5 ± 1.310.0 ± 0.1-13.5 ± 6.38.0 ± 2.16.3 ± 1.1-
Z. serrata10.0 ± 0.59.6 ± 0.63.7 ± 0.2-8.9 ± 064.3 ± 1.05.5 ± 0.0-
G. biloba8.3 ± 1.17.7 ± 2.47.2 ± 0.3-9.5 ± 1.56.3 ± 0.85.8 ± 0.5-
L. obtusifolium9.4 ± 0.916.2 ± 2.84.0 ± 0.3-11.1 ± 2.07.2 ± 0.57.7 ± 0.5-
P. × yedoensis15.4 ± 0.613.0 ± 1.05.7 ± 1.6-17.5 ± 2.913.8 ± 1.813.4 ± 1.4-
V. dilatatum10.6 ± 1.313.3 ± 1.57.0 ± 1.3-5.7 ± 1.14.9 ± 0.68.1 ± 1.1-
Table
Table 3. The leaf traits of 24 plant species in four different seasons (spring, summer, autumn, and winter).
Table 3. The leaf traits of 24 plant species in four different seasons (spring, summer, autumn, and winter).
SeasonsChl a
(mg·g−1 FW)		Chl b
(mg·g−1 FW)		TChl
(mg·g−1 FW)		RWC
(%)		pHSLA
(cm2·g−1)
J. chinensisSpring0.056 ± 0.0010.024 ± 0.0010.080 ± 0.00174.66 ± 1.155.08 ± 0.0519.06 ± 0.60
Summer0.090 ± 0.0030.030 ± 0.0030.124 ± 0.00473.45 ± 0.155.04 ± 0.0224.87 ± 0.51
Autumn0.049 ± 0.0010.020 ± 0.0000.069 ± 0.00279.28 ± 0.184.88 ± 0.0320.97 ± 0.65
Winter0.066 ± 0.0020.027 ± 0.0020.094 ± 0.00474.14 ± 0.585.70 ± 0.0116.25 ± 0.32
J. chinensis var. kaizukaSpring0.052 ± 0.0030.022 ± 0.0020.078 ± 0.00678.65 ± 0.044.75 ± 0.0119.72 ± 0.96
Summer0.058 ± 0.0010.026 ± 0.0000.084 ± 0.00177.93 ± 0.994.75 ± 0.0118.77 ± 0.48
Autumn0.053 ± 0.0020.023 ± 0.0010.076 ± 0.00491.87 ± 0.594.93 ± 0.0519.40 ± 0.16
Winter0.055 ± 0.0010.023 ± 0.0020.078 ± 0.00283.36 ± 1.125.77 ± 0.0817.02 ± 0.60
P. parvifloraSpring0.189 ± 0.0070.060 ± 0.0080.249 ± 0.01571.99 ± 1.085.00 ± 0.039.65 ± 1.36
Summer0.117 ± 0.0000.048 ± 0.0000.166 ± 0.00179.69 ± 1.475.09 ± 0.059.06 ± 0.97
Autumn0.119 ± 0.0010.045 ± 0.0000.165 ± 0.00281.71 ± 0.494.93 ± 0.0213.12 ± 0.70
Winter0.088 ± 0.0000.039 ± 0.0000.128 ± 0.00076.85 ± 0.285.85 ± 0.049.02 ± 0.30
P. densifloraSpring0.178 ± 0.0040.075 ± 0.0010.250 ± 0.00777.58 ± 1.134.62 ± 0.0314.34 ± 0.52
Summer0.122 ± 0.0010.047 ± 0.0010.184 ± 0.01486.58 ± 1.264.59 ± 0.0211.11 ± 0.67
Autumn0.106 ± 0.0010.041 ± 0.0010.146 ± 0.00196.52 ± 1.104.85 ± 0.0113.08 ± 1.24
Winter0.075 ± 0.0040.032 ± 0.0030.108 ± 0.00793.19 ± 0.506.07 ± 0.059.23 ± 0.12
C. pisiferaSpring0.157 ± 0.0030.059 ± 0.0010.216 ± 0.00481.78 ± 0.804.90 ± 0.0539.54 ± 2.07
Summer0.139 ± 0.0070.056 ± 0.0020.195 ± 0.00980.96 ± 0.534.94 ± 0.0358.19 ± 0.28
Autumn0.131 ± 0.0010.051 ± 0.0010.183 ± 0.00184.92 ± 0.315.03 ± 0.0142.99 ± 0.35
Winter0.089 ± 0.0010.038 ± 0.0010.127 ± 0.00180.65 ± 1.666.04 ± 0.1032.61 ± 0.43
T. cuspidataSpring0.124 ± 0.0200.053 ± 0.0080.140 ± 0.02475.52 ± 0.545.21 ± 0.1463.01 ± 1.89
Summer0.105 ± 0.0050.045 ± 0.0020.141 ± 0.00677.25 ± 0.984.84 ± 0.0755.18 ± 1.69
Autumn0.111 ± 0.0030.042 ± 0.0010.148 ± 0.00579.31 ± 0.365.24 ± 0.0158.30 ± 2.69
Winter0.105 ± 0.0040.051 ± 0.0020.156 ± 0.00573.02 ± 1.145.69 ± 0.0442.38 ± 0.77
A. holophyllaSpring0.105 ± 0.0090.044 ± 0.0030.135 ± 0.01174.88 ± 1.254.74 ± 0.0328.94 ± 0.58
Summer0.113 ± 0.0010.042 ± 0.0000.156 ± 0.00173.96 ± 0.244.74 ± 0.0333.90 ± 1.49
Autumn0.114 ± 0.0040.042 ± 0.0010.157 ± 0.00588.70 ± 0.574.93 ± 0.0227.12 ± 0.59
Winter0.062 ± 0.0020.030 ± 0.0010.092 ± 0.00277.56 ± 1.186.28 ± 0.0728.10 ± 0.55
P. abiesSpring0.103 ± 0.0040.042 ± 0.0030.128 ± 0.00279.12 ± 1.074.19 ± 0.0927.62 ± 1.04
Summer0.122 ± 0.0030.046 ± 0.0010.168 ± 0.00473.40 ± 0.354.19 ± 0.0931.79 ± 0.93
Autumn0.087 ± 0.0010.033 ± 0.0010.120 ± 0.00283.60 ± 0.815.06 ± 0.0433.57 ± 0.41
Winter0.101 ± 0.0000.042 ± 0.0020.142 ± 0.00280.702 ± 0.355.84 ± 0.0721.70 ± 0.41
P. strobusSpring0.094 ± 0.0070.037 ± 0.0030.147 ± 0.01262.41 ± 0.534.84 ± 0.047.80 ± 0.86
Summer0.083 ± 0.0010.035 ± 0.0010.120 ± 0.00372.78 ± 0.314.84 ± 0.043.78 ± 0.91
Autumn0.101 ± 0.0040.042 ± 0.0020.143 ± 0.00673.44 ± 0.775.05 ± 0.021.27 ± 0.11
Winter0.084 ± 0.0020.040 ± 0.0000.124 ± 0.00278.97 ± 0.465.54 ± 0.034.85 ± 0.52
P. orientalisSpring0.094 ± 0.0020.040 ± 0.0010.139 ± 0.00378.17 ± 2.584.84 ± 0.0249.33 ± 1.98
Summer0.105 ± 0.0020.045 ± 0.0010.150 ± 0.00276.43 ± 0.204.84 ± 0.0246.32 ± 1.88
Autumn0.096 ± 0.0030.039 ± 0.0010.135 ± 0.00385.22 ± 1.065.38 ± 0.0251.76 ± 0.49
Winter0.065 ± 0.0050.029 ± 0.0020.094 ± 0.00875.84 ± 1.286.16 ± 0.1539.36 ± 1.72
E. japonicaSpring0.048 ± 0.0030.024 ± 0.0010.072 ± 0.00267.96 ± 1.405.16 ± 0.0181.74 ± 1.51
Summer0.071 ± 0.0040.033 ± 0.0010.103 ± 0.00470.75 ± 0.855.16 ± 0.0182.66 ± 4.59
Autumn0.039 ± 0.0020.018 ± 0.0010.057 ± 0.00274.41 ± 0.595.31 ± 0.0391.05 ± 2.82
Winter0.044 ± 0.0060.021 ± 0.0030.065 ± 0.00960.96 ± 1.076.14 ± 0.0377.15 ± 1.44
M. denudataSpring0.096 ± 0.0050.038 ± 0.0040.145 ± 0.01467.29 ± 0.855.47 ± 0.01179.51 ± 7.27
Summer0.111 ± 0.0030.046 ± 0.0020.156 ± 0.00477.87 ± 0.315.47 ± 0.01168.66 ± 6.71
Autumn0.086 ± 0.0020.036 ± 0.0010.122 ± 0.00384.80 ± 0.136.14 ± 0.03177.88 ± 10.6
Winter000000
A. turbinataSpring0.214 ± 0.0150.043 ± 0.0050.271 ± 0.02169.42 ± 0.355.17 ± 0.03131.94 ± 2.31
Summer0.172 ± 0.0000.073 ± 0.0010.245 ± 0.00172.26 ± 0.325.17 ± 0.03145.68 ± 6.54
Autumn0.122 ± 0.0030.047 ± 0.0010.172 ± 0.00580.75 ± 1.095.56 ± 0.05123.81 ± 2.56
Winter000000
R. yedoenseSpring0.119 ± 0.0260.029 ± 0.0120.148 ± 0.03777.55 ± 0.415.21 ± 0.04165.65 ± 1.17
Summer0.165 ± 0.0060.076 ± 0.0050.261 ± 0.01887.68 ± 1.785.18 ± 0.07163.55 ± 2.48
Autumn0.165 ± 0.0040.066 ± 0.0010.230 ± 0.00686.44 ± 0.405.47 ± 0.03151.35 ± 1.82
Winter000000
H. syriacusSpring0.128 ± 0.0130.026 ± 0.0040.154 ± 0.01380.34 ± 0.655.63 ± 0.03160.35 ± 4.51
Summer0.173 ± 0.0120.071 ± 0.0060.244 ± 0.01778.41 ± 0.795.63 ± 0.03147.46 ± 4.12
Autumn0.157 ± 0.0020.071 ± 0.0020.228 ± 0.00381.45 ± 0.886.15 ± 0.02151.61 ± 3.38
Winter000000
A. palmatumSpring0.075 ± 0.0070.026 ± 0.0120.070 ± 0.00785.26 ± 0.194.71 ± 0.02152.04 ± 5.05
Summer0.164 ± 0.0150.071 ± 0.0020.242 ± 0.01291.30 ± 0.274.71 ± 0.02193.06 ± 5.44
Autumn0.168 ± 0.0030.068 ± 0.0010.237 ± 0.00392.00 ± 0.474.99 ± 0.09201.17 ± 6.55
Winter000000
C. chinensisSpring0.193 ± 0.0080.054 ± 0.0070.269 ± 0.01561.45 ± 1.754.31 ± 0.05159.38 ± 13.53
Summer0.191 ± 0.0040.085 ± 0.0020.274 ± 0.00665.69 ± 0.344.42 ± 0.06156.05 ± 17.76
Autumn0.166 ± 0.0000.070 ± 0.0010.234 ± 0.00175.35 ± 0.505.44 ± 0.01253.01 ± 21.21
Winter000000
C. officinalisSpring0.127 ± 0.0290.055 ± 0.0140.182 ± 0.04264.92 ± 0.165.84 ± 0.02156.65 ± 2.40
Summer0.150 ± 0.0050.065 ± 0.0010.209 ± 0.00373.81 ± 0.775.84 ± 0.02210.40 ± 21.70
Autumn0.081 ± 0.0060.036 ± 0.0020.117 ± 0.00873.75 ± 0.866.25 ± 0.04121.68 ± 3.91
Winter000000
A. triflorumSpring0.194 ± 0.0190.070 ± 0.0150.287 ± 0.03568.34 ± 4.524.41 ± 0.02214.34 ± 7.11
Summer0.217 ± 0.0230.100 ± 0.0090.317 ± 0.03175.56 ± 0.854.39 ± 0.04238.45 ± 9.92
Autumn0.152 ± 0.0050.063 ± 0.0020.212 ± 0.00871.01 ± 0.315.81 ± 0.01205.55 ± 8.00
Winter000000
Z. serrataSpring0.177 ± 0.0050.061 ± 0.0020.237 ± 0.00652.93 ± 3.925.15 ± 0.01203.19 ± 0.53
Summer0.192 ± 0.0180.078 ± 0.0060.269 ± 0.02361.44 ± 0.935.15 ± 0.01174.44 ± 2.83
Autumn0.233 ± 0.0300.102 ± 0.0100.374 ± 0.03556.92 ± 0.405.86 ± 0.02224.08 ± 3.65
Winter000000
G. bilobaSpring0.093 ± 0.0030.029 ± 0.0020.122 ± 0.00375.00 ± 0.065.00 ± 0.09129.80 ± 5.15
Summer0.074 ± 0.0040.034 ± 0.0030.107 ± 0.00672.13 ± 0.055.00 ± 0.09131.70 ± 1.51
Autumn0.053 ± 0.0020.024 ± 0.0000.074 ± 0.00180.03 ± 0.675.69 ± 0.03156.01 ± 1.22
Winter000000
L. obtusifoliumSpring0.203 ± 0.0050.070 ± 0.0030.257 ± 0.01769.74 ± 2.665.14 ± 0.02122.36 ± 2.48
Summer0.174 ± 0.0040.063 ± 0.0020.237 ± 0.00566.93 ± 0.715.14 ± 0.02157.87 ± 13.67
Autumn0.156 ± 0.0110.065 ± 0.0030.240 ± 0.01372.35 ± 3.705.34 ± 0.02207.37 ± 3.50
Winter000000
P. × yedoensisSpring0.137 ± 0.0020.049 ± 0.0020.186 ± 0.00475.81 ± 0.225.03 ± 0.0095.33 ± 1.98
Summer0.134 ± 0.0050.055 ± 0.0040.189 ± 0.00876.55 ± 0.805.03 ± 0.00110.75 ± 3.71
Autumn0.124 ± 0.0190.042 ± 0.0010.146 ± 0.00481.83 ± 0.435.38 ± 0.01120.18 ± 3.51
Winter000000
V. dilatatumSpring0.164 ± 0.0210.039 ± 0.0060.203 ± 0.02846.36 ± 1.825.60 ± 0.01216.28 ± 11.07
Summer0.212 ± 0.0100.091 ± 0.0040.303 ± 0.01464.15 ± 1.485.60 ± 0.01251.32 ± 1.95
Autumn0.146 ± 0.0070.063 ± 0.0030.209 ± 0.01062.67 ± 0.785.68 ± 0.01302.54 ± 4.60
Winter000000
Chl a: chlorophyll a concentration, Chl b: chlorophyll b concentration, TChl: total chlorophyll concentration, RWC: relative leaf water content, pH: leaf extract pH, and SLA: specific leaf area.
Table
Table 4. ANOVA analysis of PM accumulation on the leaf and leaf traits of 24 plant species in the four seasons (spring, summer, autumn, and winter).
Table 4. ANOVA analysis of PM accumulation on the leaf and leaf traits of 24 plant species in the four seasons (spring, summer, autumn, and winter).
Species
(F23,192)		Seasons
(F3,192)		Species × Season
(F69,192)
sPM (10–100)155.44 ***20.46 ***5.77 ***
sPM (2.5–10)149.94 ***47.48 ***38.04 ***
wPM (10–100)229.74 ***34.54 ***13.88 ***
wPM (2.5–10)27.95 ***9.71 ***9.39 ***
Chl a47.32 ***750.56 ***23.66 ***
Chl b29.11 ***498.36 ***20.88 ***
TChl48.89 ***747.12 ***27.2 ***
RWC576.54 ***8009.28 ***297.33 ***
pH882.41 ***19134.2 ***1415.78 ***
SLA465.06 ***2098.27 ***84.38 **
Levels of significance: ** p < 0.01, *** p < 0.001. PM (10–100): particulate matter with diameter 10–100 µm, PM (2.5–10): particulate matter with diameter 2.5–10 µm, sPM: particulate matter on the leaf surface, wPM: particulate matter in the wax layer, Chl a: chlorophyll a concentration, Chl b: chlorophyll b concentration, TChl: total chlorophyll concentration, RWC: leaf relative water content, pH: leaf extract pH, SLA: specific leaf area.
Table
Table 5. Pearson correlation analysis of the accumulation of different fractions of particulate matter on leaf and leaf traits of 24 plant species in the four seasons.
Table 5. Pearson correlation analysis of the accumulation of different fractions of particulate matter on leaf and leaf traits of 24 plant species in the four seasons.
PM SizeChl a Chl b TChl RWC pH SLA
SpringsPM (10–100)−0.012 0.106 0.046 −0.037 −0.204 −0.554***
sPM (2.5–10)0.035 0.110 0.069 0.141 −0.284*−0.548***
wPM (10–100)−0.148 0.066 −0.070 0.047 −0.269*−0.633***
wPM (2.5–10)0.087 0.095 0.127 −0.007 0.016 −0.154
SummersPM (10–100)−0.285*−0.295*−0.266*0.155 −0.148 −0.484***
sPM (2.5–10)−0.196 −0.168 −0.183 0.314*−0.200 −0.381***
wPM (10–100)−0.344**−0.359**−0.332**0.062 −0.244*−0.537***
wPM (2.5–10)−0.306**−0.329**−0.300*0.138 −0.165 −0.471***
AutumnsPM (10–100)−0.123 −0.136 −0.131 0.055 −0.313**−0.445***
sPM (2.5–10)−0.175 −0.210 −0.181 0.182 −0.479***−0.579***
wPM (10–100)−0.177 −0.214 −0.189 0.190 −0.477***−0.577***
wPM (2.5–10)−0.134 −0.139 −0.137 −0.025 −0.258*−0.331**
WintersPM (10–100)0.231 0.287 0.252 0.200 −0.360 −0.559***
sPM (2.5–10)0.177 0.250 0.202 0.107 −0.459 −0.472**
wPM (10–100)0.142 0.209 0.165 0.269 −0.423 −0.545***
wPM (2.5–10)0.149***0.217***0.172***0.214 −0.413 −0.492**
Levels of significance: * p < 0.05, ** p < 0.01, *** p < 0.001. PM (10–100): particulate matter with diameter 10–100 µm, PM (2.5–10): particulate matter with diameter 2.5–10 µm, sPM: particulate matter on the leaf surface, wPM: particulate matter in the wax layer, Chl a: chlorophyll a concentration, Chl b: chlorophyll b concentration, TChl: total chlorophyll concentration, RWC: leaf relative water content, pH: leaf extract pH, SLA: specific leaf area.
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Bui, H.-T.; Odsuren, U.; Kim, S.-Y.; Park, B.-J. Seasonal Variations in the Particulate Matter Accumulation and Leaf Traits of 24 Plant Species in Urban Green Space. Land 2022, 11, 1981. https://doi.org/10.3390/land11111981

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Bui H-T, Odsuren U, Kim S-Y, Park B-J. Seasonal Variations in the Particulate Matter Accumulation and Leaf Traits of 24 Plant Species in Urban Green Space. Land. 2022; 11(11):1981. https://doi.org/10.3390/land11111981

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Bui, Huong-Thi, Uuriintuya Odsuren, Sang-Yong Kim, and Bong-Ju Park. 2022. "Seasonal Variations in the Particulate Matter Accumulation and Leaf Traits of 24 Plant Species in Urban Green Space" Land 11, no. 11: 1981. https://doi.org/10.3390/land11111981

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