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Article

A Study on the Dust Retention Effect of the Vegetation Community in Typical Urban Road Green Spaces—In the Case of Ying Tian Street in Nanjing City

by
Qianqian Sheng
1,2,3,4,*,
Yuanhao Guo
1,2,
Jiani Lu
1,2,
Shuang Song
1,2,
Weizheng Li
5,
Ruizhen Yang
6 and
Zunling Zhu
1,2,3,4,7,*
1
College of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, China
2
Co-Innovation Center for the Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
3
Jin Pu Research Institute, Nanjing Forestry University, Nanjing 210037, China
4
Research Center for Digital Innovation Design, Nanjing Forestry University, Nanjing 210037, China
5
Advanced Analysis and Testing Center, Nanjing Forestry University, Nanjing 210037, China
6
Nanjing Sky Hunt Data Technology Co., Ltd., Nanjing 210037, China
7
College of Art and Design, Nanjing Forestry University, Nanjing 210037, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(7), 2656; https://doi.org/10.3390/su16072656
Submission received: 7 February 2024 / Revised: 14 March 2024 / Accepted: 19 March 2024 / Published: 24 March 2024
Browse Figures
Versions Notes

Abstract

:
This study aimed to investigate the association between the plant community structure, leaf surface microstructure, nutrient element content, and the dust-retention capacity of garden plants in urban road green spaces. The plant community located along Ying Tian Street in Nanjing City was selected as the focal point of the investigation. Random sampling was performed on the urban road green spaces, determining the amount of dust trapped in plant leaves. Subsequently, the microstructure of the leaf surface was observed, and the content of nutrient elements in the plant leaves was determined. The study also entailed an analysis of the interrelationships between the leaf surface microstructure, plant nutrient element content, and the dust-retention ability of the plants. The findings of this study revealed notable variations in the dust-retention capacity of garden plants and the community structure observed along Ying Tian Street. Among the tree species, Cedrus deodara and Ginkgo biloba exhibited a remarkable dust-retention ability per unit leaf area. Among the shrub species, Abelia × grandiflora and Loropetalum chinense displayed a strong dust-retention capacity per unit leaf area. Similarly, Ophiopogon japonicus and Cynodon dactylon exhibited a robust dust-retention ability per unit leaf area among the herbaceous plants. Furthermore, the dust-retention ability of the plants exhibited a strong positive correlation with the dimensions of leaf stomata, specifically the length and width, while displaying a moderate positive correlation with the width of grooves on the upper and lower surfaces of the leaves. Conversely, the thickness of the leaves did not exhibit a significant correlation. Additionally, the nitrogen content of the leaves exerted a significant influence on the dust-retention ability of the plants (p < 0.05), although the phosphorus and potassium content factors did not exhibit a significant influence (p > 0.05). Based on the findings, it is recommended to prioritize the utilization of plants with robust dust-retention abilities, such as C. deodara, A. grandiflora, O. japonicus, and C. dactylon, and implement a mixed planting approach encompassing a combination of trees, shrubs, and herbaceous plants within urban road green spaces.

1. Introduction

Due to the rapid urbanization process in our country, urban functions and structures are continuously evolving. The increased frequency of vehicle usage and the rise in industrial emissions, as well as coal combustion, have contributed to a gradual elevation in atmospheric pollutant levels. Such atmospheric pollution poses significant threats to human health [1,2]. In the context of reducing particulate pollution and enhancing air quality, urban road green spaces play an indispensable role [3,4]. Notably, plants offer not only aesthetic benefits to the environment but also effectively capture particulate matter, leading to a reduction in the concentration of total suspended particles (TSP) in the atmosphere through a process of self-purification. This, in turn, mitigates the adverse impacts of particulate matter on human health [5]. In cities, the ability of plants to trap dust is directly related to air quality. Good air quality can effectively reduce the probability of respiratory diseases among people in cities [6,7]. Therefore, research on the dust-trapping ability of plants is crucial to the sustainable development of our cities. Plants play a vital role in the sustainable development of cities. Moreover, different configurations of plant communities exhibit distinct trapping capacities. For example, the combined presence of trees, shrubs, and grass in road green spaces can obstruct TSP at rates ranging from 26% to 35%. Plants can absorb particulate matter and harmful gases due to distinctive features such as rough leaf surfaces, stomata, ridges, trichomes, and adhesive fluids. Furthermore, they can enhance the deposition of particulate matter and impede its dispersion through varying greening structures, suitable track widths, and optimal closure density [8,9].
Numerous studies have demonstrated the link between the adsorption capacity of plant leaves towards particulate matter and specific morphological attributes of leaves, such as roughness, wettability, wax content, trichomes, and stomata characteristics [10]. Sun Yingdu [11] and other researchers have elucidated the influence of leaf roughness, as well as the shape and quantity of trichomes, on the dust trapping capability of leaves. The process of leaf dust-trapping involves three concurrent mechanisms: retention, adhesion, and attachment. Zheng Guiling [12] and other investigations have established a significant positive correlation between the presence of trichomes on leaf surfaces and both the maximum rate of particulate matter (PM) retention and the natural retention rate. In a similar vein, research conducted by Li Yaohua [13] and colleagues has underscored the impact of leaf surface stomatal characteristics, trichome length, and groove width on the retention efficacy of leaves towards particulate matter of varying sizes. Leaves possessing more prominent stomatal features and a higher stomatal density tend to exhibit a greater accumulation of particulate matter on their surfaces. This phenomenon can be attributed to the increased transpiration rate facilitated by stomata, which renders hydrophilic particles more prone to adsorption onto leaf surfaces. In contrast, wider groove widths on leaf surfaces lead to a reduced presence of particulate matter, specifically impeding the retention of particles within the PM1–3 size range. Yan Qian [14] and other researchers have investigated Magnolia wangchunensis and Japanese late cherry, revealing that the dust-trapping capacity of plant leaves on a single leaf area is primarily influenced by leaf morphology, particularly leaf size. However, there is no observed correlation between leaf morphology parameters and the dust-trapping capacity per unit area. Additionally, the leaf surface structure plays a vital role in determining the dust-trapping capacity per unit area. Rough leaf surfaces characterized by numerous folds, grooves, and protrusions, in conjunction with the presence of stomata or wax, facilitate dust retention [15]. Investigations conducted by Zhu Liqiong [16] and colleagues have found that soft and drooping branches do not favor dust retention, whereas trichomes on leaves, serrations on leaf edges, fewer primary lateral veins, dispersed terminal veins, and upward or downward convexity of leaf veins all enhance the dust-trapping ability of plant leaves. Buccolieri [17] and other researchers utilized OpenFOAM CFD SUPPORT OF4Win software to assess the impact of trees on street ventilation. Their study demonstrated that winds parallel to the road direction promote particle deposition and dust retention by plants, subsequently reducing air pollution concentration. Conversely, winds perpendicular to the road direction can disperse particles captured by plants, thus undermining dust retention efforts.
The dust-retention capability of plants is a result of the combined effects of various environmental factors. Chen Yingjia et al. [18] have identified three categories of influencing factors for the dust-retention capability of different plants, namely plant factors, dust factors, and environmental factors. Moreover, Shao et al. [19] have demonstrated the direct correlation between the ability of plants to retain particulate matter (PM) and the microstructural characteristics of their leaves. These characteristics encompass the interplay of various factors, including grooves, folds, filamentous projections, trichomes, and wax on the surface of the plant. Ren et al. [20] showed that the nitrogen content of plant leaves had a certain effect on the activity of nitrogen metabolism-related enzymes, and nitrogen metabolism was positively correlated with photosynthesis, and the enhanced photosynthesis of plant leaves helped to increase the stomatal conductance of leaves, which had a certain impact on the dust retention ability of plants. Perini et al. [21] have proposed that the impact of vertical greening systems on particle concentration is contingent upon the specific attributes of plant species, with the selection of appropriate species greatly augmenting the dust-retention capability of such systems. Furthermore, Sæbø [22] and Dzierzanowski [23] have discovered that leaf surface features, such as trichomes and wax content, constitute the primary factors influencing the dust-retention capacity of plants.
Research on the dust-retention capability of plant communities in road green spaces has been relatively limited compared to the predominant focus on studying the dust-trapping ability of single plant species in industrial areas and parks [24]. Trees, with their larger leaf surface area and distinctive physical properties, can function as biological filters, proficiently removing a greater quantity of airborne pollutants and thereby enhancing air quality in polluted regions. The purification outcomes may differ according to the specific arrangements of vegetation in road green spaces [25].
The present study aims to assess the dust-trapping efficacy of garden plants in Ying Tian Avenue, Nanjing, by analyzing Nanjing’s current report on particulate pollutants and relevant literature. Furthermore, the research endeavors to survey the robust dust-trapping capabilities of garden plants and plant communities in typical urban road green spaces in Nanjing. An examination of the current utilization of plant species in Nanjing will be conducted to discern the existing state of plant application. Additionally, the relationship between leaf surface phenotypic traits, functional traits, and particulate matter retention capacity of plants in road green spaces will be investigated through experimental research. The analysis of data about the mass of particulate matter retained per unit leaf area will offer further insights into the dust-trapping abilities of green vegetation. The findings of this study, thus, aim to serve as a reference for the selection and configuration of urban green spaces, as well as the evaluation of dust-trapping ecological services provided by green trees. Furthermore, the research seeks to contribute to the development of new models for the configuration of urban road green spaces while also providing scientific and theoretical support for urban landscaping and the improvement of the living environment in cities, committing to urban renewal and sustainable development, as well as to contribute to the protection of urban ecological environment and the sustainable development of the Earth’s environment.

2. Materials and Methods

2.1. Study Area Overview

Nanjing, situated in the lower reaches of the Yangtze River, possesses a coastline and a subtropical monsoon climate, characterized by distinct four seasons, with relatively short spring and autumn periods and prolonged winters and summers. The city exhibits a moderate temperature range and receives ample rainfall. Serving as the central hub of the Yangtze River Delta region, Nanjing boasts one of the highest urbanization rates (Figure 1). Consequently, urbanization significantly impacts the local climate of Nanjing and the wider Yangtze River Delta. The chosen sampling point for this research lies on Ying Tian Avenue in Jianye District, Nanjing, at coordinates 118°46′1.78″ E and 32°1′8.17″ N. Ying Tian Avenue spans approximately 6.5 km in a north–south direction and is flanked by high-density buildings, hosting a dense population. The road is characterized by heavy traffic flow (during peak hours, the traffic volume on the ramp is 1900 cars per hour) and serves as a bustling metropolitan corridor. Commercial and office buildings dominate the area, accommodating an array of pedestrians and diverse vehicle types. The presence of diverse tree species and an overhead bridge further exemplify its typicality as an urban road in Nanjing.

2.2. Materials and Methods

On 13 April 2023, which was the seventh day after rainfall in which the cumulative rainfall reached more than 27 mm, a comprehensive survey was conducted to assess the composition of vegetation in the traffic greenery found on both sides of the road. The sampling process was carried out within a single day, during which the weather was sunny, without exceptional conditions such as heavy winds or rainfall. Three replicate samples were selected for each plant species under examination, ensuring that the sampled plants were consistent regarding trunk diameter, tree height, tree age, crown width, and overall growth status. Samples were collected uniformly from the peripheral, upper, middle, and lower parts of the tested plants, with 15 to 30 plant leaves being collected at multiple points to ensure sufficient representation of dust deposition. The study involved the selection of specific sampling points to systematically document the presence of various plant layers, including the tree layer, shrub layer, and herbaceous layer. Thirteen distinct plant communities were identified, exhibiting identical plant species combinations but varying distances from the road. These communities consisted of 2 shrub communities, 3 tree communities, 2 shrub–grass communities, 5 tree–shrub communities, and 3 tree–shrub–grass communities (Table 1). Each community was strategically positioned in different roadside environments, including locations beneath overpasses and along both sides of the road. To further enhance the comprehensiveness of the study, numerous leaf traits were meticulously examined for each tree species. These traits encompassed measurements of leaf area as well as a comprehensive assessment of functional characteristics associated with the leaves.

2.3. Data Processing

2.3.1. Dust Retention per Unit Leaf Area of Plants

The collected tree leaves were carefully sealed in tissue bottles and fully submerged in ionized water, allowing them to soak for a duration of 4 h [26]. Deionized water, with a known weight of W1, was utilized for the leaf immersion process. The deionized water was filtered through a previously weighed filter paper. Consequently, the filtered paper, bearing the imprints of the filtrate, was cautiously transferred to a clean and dry Petri dish. The dish was appropriately labeled with the corresponding plant species and time and subsequently placed in a temperature-controlled oven set at 60 °C for a period of 24 h. Upon completion of the drying process, an electronic balance, precise to an accuracy of 0.0001 g, was employed to weigh the filter paper, and the recorded weight was denoted as W2, serving as the basis for subsequent analysis. Additional tree leaves, acquired for supplementary purposes, were gently dried using absorbent paper towels. The leaf area meter was employed to measure the total leaf area for each plant species. This information, integrated with the measured dust retention and the total leaf area, facilitated the computation of the plant’s specific leaf area [27].
G = (W2 − W1)/S
where G represents the dust retention per unit leaf area of the plant, W2 represents the weight of the filter paper after filtration and drying, W1 represents the weight of the filter paper itself, and S represents the area of the collected leaves.
SLA = LA/DW
where SLA represents the specific leaf area of the plant, LA represents the leaf area, and DW represents the dry weight of the leaves.

2.3.2. Dust Retention in Different Plant Community Structures

The various plant community structures can be classified and designated as follows: shrub community: community A; shrub–grass community: community B; tree–shrub–grass community: community C; tree–shrub community: community D; and tree community: community E. To ensure methodological consistency, equivalent areas of road green spaces were systematically demarcated. Subsequently, an equal number of leaves were systematically collected from each specific plant community, including the tree–shrub–grass, tree–shrub, and tree communities. Dust retention levels were quantified utilizing a standardized method designed for determining the total dust retention in plants. Multiple measurements were conducted for each community grouping, denoted by the corresponding letter designation. Subsequently, the average value and standard deviation were meticulously calculated based on the collected data.

2.3.3. Nitrogen, Phosphorus, and Potassium Contents of Plant Leaves

The determination of nitrogen content in plant leaves was conducted using the Kjeldahl digestion method, followed by colorimetric measurement. Additionally, a series of standard solutions with varying nitrogen concentrations (0, 0.5, 1, 2, 3, 4, and 5 mL) were prepared and transferred to 50 mL volumetric flasks. Similar coloration procedures were performed on these standard solutions, enabling the construction of a standard curve. To measure the phosphorus content in plant leaves, the molybdenum antimony anti-coloration method were employed. Concurrently, a set of standard solutions with different phosphorus concentrations (0, 1, 2, 3, 4, 5, and 6 mL) were prepared and transferred to 50 mL volumetric flasks. Following the same coloration procedure, a standard curve were generated. For the determination of potassium content in plant leaves, the flame photometry method was utilized. Likewise, a series of standard solutions with varying potassium concentrations (0, 1, 2.5, 5, 10, 20, and 30 mL) were prepared and transferred to 50 mL volumetric flasks. Subsequently, the standard solutions underwent the flame photometry procedure, allowing for the construction of a standard curve.
W = [(c × V × t)/m × 106] × 1000
where W represents the total nitrogen (WN), total phosphorus (WP), or total potassium (WK) content. c represents the concentration of the coloration solution for nitrogen or phosphorus obtained from the working curve or the concentration of the coloration solution for potassium measured from the flame photometer, V represents the volume of the coloration solution, t represents the multiple of the aliquot taken, and m represents the mass of the dried sample.

2.3.4. Correlation between Environmental Factors and Plant Dust Retention Capacity

This study aimed to investigate the environmental factors, namely climate and soil conditions that potentially affect the level of dust accumulation in road green spaces. The analysis was conducted by referring to existing reports on particulate matter concentration obtained from monitoring websites dedicated to relevant environmental factors. Following this, the factors that have an impact on dust retention were identified, and various variable control methods were employed to establish the correlation between these environmental factors and the ability to retain dust. In doing so, relevant studies on the dust retention capabilities of plants were also taken into consideration.

2.3.5. Observation of Microstructure

Multiple healthy leaves were collected from each plant species for further analysis. To ensure accuracy, the main veins were avoided, and 5 mm × 5 mm squares were randomly cut from the leaves. The leaf surface and cross-sectional structure were observed and photographed using a scanning electron microscope, specifically the QUANTA 200 model. Image Pro Plus software (6.0) was then utilized to quantitatively measure various parameters, including leaf thickness, stomatal length, and width, as well as leaf groove width.

2.3.6. Data Processing

EXCEL 2019 was employed for organizing and conducting calculations about unit leaf area dust retention and nitrogen-phosphorus content, to facilitate subsequent comparisons. For significance analysis and one-way analysis of variance, SPSS 26 was utilized. Additionally, Origin 2023 was used to generate correlation bar charts and standard curves.

3. Results and Discussion

3.1. Analysis of the Impact of Plant Species and Community Structure on Dust Retention

Differences in dust retention capacities among various plants can be attributed to their distinctive growth habits, while varying community structures also contribute to differences in dust retention capacities. As illustrated in Figure 2, the average unit leaf area dust retention of deciduous trees ranks as follows in descending order: C. deodara > G. biloba > O. fragrans > C. camphora > L. lucidum > A. palmatum > T. fortunei > C. chinensis > P. acerifolia. C. deodara exhibits the highest average unit leaf area dust retention with a mean value of 150.37 g/m2, whereas P. acerifolia demonstrates the lowest average value of 0.86 g/m2 (Figure 2a). Regarding shrubs, the unit leaf area dust retention is ranked in descending order as follows: A. grandiflora > L. chinense > L. quihoui > L. vicaryi > R. pulchrum > P. tobira > E. japonicus > P. fraseri > F. japonica > A. japonica. A. grandiflora exhibits the highest unit leaf area dust retention with an average value of 53.51 g/m2, while A. japonica shows the lowest with an average value of 3.20 g/m2 (Figure 2b). The unit area dust retention of herbaceous plants is ranked in descending order as follows: O. japonicus > C. dactylon > P. annua > E. pectinatus > A. elatius. Notably, O. japonicus demonstrates the highest unit area dust retention with a value of 65.23 g/m2, while A. elatius displays the lowest with a value of 4.85 g/m2 (Figure 2c). Concerning plant community structures, dust retention is ranked in descending order as follows: tree–shrub–grass community > tree–shrub community > shrub–grass community > shrub community > tree community (Figure 2d).
Significant variations exist in dust retention capacities across different types of plants, namely trees, shrubs, and herbaceous plants. The lower dust-holding capacity of Platanus erata is inconsistent with most other studies [8]. This may be because the specimens were collected in April, the plain trees were not fully developed yet, and most of the leaves were young leaves, so the amount of dust retained was less. The unit leaf area of dust retention can differ by orders of magnitude among various species, and notable distinctions are observed in dust retention capabilities among diverse community structures. Coniferous trees exhibit higher dust retention abilities compared to broad-leaved trees, consistent with the findings of Chen et al. [28] and Steinparzer [29]. G. biloba demonstrates a robust dust retention capacity, as corroborated by the research of Jinqiang [30]. Among the plant community structures, shrub communities display the highest dust retention ability among single-species plant communities, aligning with the investigation conducted by Mengfan [31]. The disparity in dust retention between shrub–grass and tree–shrub community structures is not statistically significant. However, the addition of trees or shrubs to the community significantly enhances dust retention within the tree–shrub–grass community structure. To some extent, the greater the diversity in plant community structure and the more complex the community hierarchy, the greater the dust retention [32]. A comparison of dust retention levels reveals a considerable enhancement in dust retention when trees are added to shrub communities, as opposed to shrub–grass communities. This phenomenon may be attributed to the blocking effect of the tall tree canopy, which partially obstructs sunlight, thereby improving the microclimate within the local community. This improvement manifests as increased humidity and an augmented concentration of negative ions. Notably, there exists a significant positive correlation between negative ion concentration and the ability of plants to retain dust, consequently bolstering the overall dust retention capacity of the community [33]. Conversely, when considering the dust retention ability in tree communities alone, it is found to be the lowest among the studied plant community types. Consequently, based on this contrast, the subsequent section on the influence of leaf nitrogen, phosphorus, and potassium content on dust retention abilities will employ trees as a representative example.

3.2. Analysis of the Correlation between Nitrogen, Phosphorus, and Potassium Content in Plant Leaves and the Amount of Dust Retention

The addition of trees to shrub communities and shrub–grass community structures results in a discernible augmentation in dust retention. However, the dust retention capacity of the tree community in isolation is comparatively lower. Based on this disparity, the subsequent section focusing on the influence of leaf nitrogen, phosphorus, and potassium content on dust retention ability will utilize trees as the primary example. Referring to Figure 3, the nitrogen content per unit leaf area of plants follows the following order: G. biloba > L. lucidum > C. camphora > O. fragrans > C. deodara > P. acerifolia > A. palmatum. G. biloba exhibits the highest nitrogen content per unit leaf area, with a mean value of 76.91 μg/m2, while A. palmatum demonstrates the lowest, with an average of 4.49 μg/m2. Regarding phosphorus content per unit leaf area, the order among plants is as follows: O. fragrans > C. camphora > L. lucidum > C. deodara > A. palmatum > P. acerifolia > G. biloba. O. fragrans displays the highest phosphorus content per unit leaf area, with a mean value of 11.65 μg/m2, while G. biloba exhibits the lowest, with an average of 0.77 μg/m2. It should be noted that evergreen plants generally possess a higher phosphorus content compared to deciduous plants. Concerning potassium content per unit leaf area, the order among plants is P. acerifolia > O. fragrans > L. lucidum > G. biloba > C. camphora > C. deodara > A. palmatum. P. acerifolia showcases the highest potassium content per unit leaf area, with a mean value of 245.92 μg/m2, whereas A. palmatum showcases the lowest, with an average of 19.25 μg/m2.

3.3. Analysis of the Influence of Plant Leaf Microsurface Features on Dust Retention

This article illustrates the selection of representative plants with contrasting dust-retention capabilities across different plant types. Based on the examination of the microstructural features of the leaf surfaces in Figure 4, it is evident that C. deodara possesses a thicker cuticle layer, a rougher surface with striated patterns, and is adorned with waxy scales or granular protrusions. The irregular polygonal shape of the leaf cross-section forms grooves of specific depth and width, thereby facilitating a larger contact area for dust particles and enhancing dust-retention capacity [34]. G. biloba leaf exhibits distinct cell contours, which precede the protrusions and enable the retention of a significant amount of particles [34]. P. acerifolia leaves are covered with numerous soft hairs and are mainly attached to the surface and primary veins. The prominent primary veins and dense trichomes effectively retain particles. However, contrary to expectations, the P. acerifolia leaf, as shown in Figure 2, demonstrates the lowest dust-retention capability per unit leaf, measuring 0.85 g/m2. This might be ascribed to the fact that the leaves of P. acerifolia observed in early April are predominantly new leaves, leading to diminished dust retention. This outcome deviates from the findings of Qiao Guanhao [35] and Wang Qin [8]. Alternatively, inaccuracies in the sample size of P. acerifolia could account for this discrepancy. The T. fortunei leaf surface is characterized by its smoothness and relatively even distribution of stomata, resulting in limited adhesive power for dust particles. Additionally, the adhered dust particles are readily removed by rainwater, resulting in reduced dust retention [36]. A. grandiflora leaves possess a rough surface with numerous linear protrusions, and the wider grooves on the leaf surface favor the accumulation and adsorption of dust particles, thereby increasing the contact area between the leaf surface and the particles to a certain extent [37,38]. L. chinense leaves not only exhibit numerous small protrusions but also possess many star-shaped hairs, enhancing their ability to retain dust. The leaves of O. japonicus feature sunken stomata and adjacent folds [39], while C. dactylon leaves present a rough surface characterized by regularly dense dot-like protrusions and trichomes, all of which collectively contribute to the retention of dust particles on the leaf surface. Plants with strong dust retention capabilities not only have hairs or ravines, but the length and width of the stomata on their leaf surfaces are generally larger. However, when there is a lot of particulate matter on the surface of plant leaves and the particulate matter covers the plant leaves, the ability of the leaf surface microstructure to retain particulate matter will be reduced to a certain extent. So, what has a greater impact on the dust retention ability of plant leaves currently needs further research.

3.4. Analysis of the Correlation between Nitrogen, Phosphorus, and Potassium Content, the Microstructure of Plant Leaves, and Dust Retention Ability

As depicted in Figure 5, there exists a robust positive correlation between the dust-retention capability of plants and the dimensions (length and width) of leaf stomata. Furthermore, observations reveal that within a range of 4.06–35.71 μm, the dust-retention potential of plants also exhibits a substantial positive correlation with the width of the epidermal grooves and the width of the subepidermal grooves on the leaf surface, aligning with the findings of Zhao Bing [40] and other researchers. G. biloba increased stomatal width and length, thereby manifesting a heightened dust-retention capacity per unit leaf area. Conversely, T. fortunei exhibits a non-negligible stomatal width and length, yet its dust-retention quantity per unit leaf area is minimal, thereby indicating that the dust-retention capability of plants is influenced by diverse factors, including stomatal density and leaf surface smoothness [41]. The correlation between the dust-retention prowess of plants and leaf thickness does not exhibit significant statistical significance.
The dust-retention capacity of plants exhibits a strong positive correlation with leaf nitrogen content, indicating that the nitrogen content factor exerts a significant influence on the dust-retention capability of plants (p ≤ 0.05). However, no significant correlation is observed between the dust-retention ability of plants and leaf phosphorus or potassium content. To a certain extent, an increase in the nitrogen content of plants is associated with a gradual enhancement of their dust-retention prowess. This relationship can be attributed to the potential correlation between plant nitrogen content and respiratory function [42]. As respiratory function strongly influences leaf stomata, it consequently affects the dust-retention capability of plants.

4. Conclusions

This study employed a comprehensive approach involving field investigations, sampling, experimental analysis, and data analysis to examine the dust-capturing efficacy of 24 species of traffic greening plants and 13 distinct plant communities in Ying Tian Avenue, Nanjing. Quantification of the dust-trapping quantity and specific leaf area was conducted for each plant or plant community structure. Moreover, the study observed leaf phenotypic traits and analyzed functional traits derived from leaf nitrogen, phosphorus, and potassium elements, taking into account the influence of environmental factors on a plant’s dust-trapping ability. The key findings of this investigation are summarized as follows:
(1) The ranking of the dust trapping ability of the green plants and community structures in Ying Tian Avenue is as follows: Arbor, C. deodara > G. biloba > O. fragrans > C. camphora > L. lucidum > A. palmatum > T. fortunei > C. chinensis > P. acerifolia. Shrub, A. grandiflora > L. chinense > L. quihoui > L. vicaryi > R. pulchrum > P. tobira > E. japonicus > P. fraseri > F. japonica > A. japonica. Herb, O. japonicus > C. dactylon > P. annua > E. pectinatus > A. elatius. Community structure, tree–shrub–grass community > tree–shrub community > shrub–grass community > shrub community > tree community. In the context of urban road greening, the utilization of C. deodara, G. biloba, A. grandiflora, L. chinense, O. japonicus, and C. dactylon is recommended as noteworthy tree species for road greening endeavors. These species exhibit a notable capacity for mitigating urban dust particulate pollution, thereby exerting a positive influence on environmental advantages and aesthetic enhancements. Additionally, in the context of urban road greening similar to Ying Tian Avenue, prioritizing the adoption of tree–shrub–herb plant community typologies is advisable, given its propensity to enhance plant diversity and effectively amplify the dust-trapping capability of the plant community, which is conducive to sustainable urban development.
(2) The microstructural characteristics of the leaf surface exert a pronounced influence on the dust-capturing capacity of plants. Plant species featuring rough leaf surfaces, characterized by concave grooves and trichomes, typically exhibit enhanced capabilities for trapping dust particles. Observations revealed that within a range of 4.06–35.71 μm, an increase in stomatal length and width, as well as wider epidermal grooves, positively correlates with an augmented dust-capturing ability of the plant.
(3) The nutrient composition within leaves exhibits a discernible impact on a plant’s dust-trapping capacity. In particular, the nitrogen content factor significantly influences the plant’s dust-trapping ability, yielding statistically significant results (p ≤ 0.05). To a certain extent, an increase in nitrogen content within plants corresponds to a gradual enhancement of their dust-trapping efficacy.

Author Contributions

Conceptualization, Q.S., R.Y. and Z.Z.; Methodology, Q.S., Y.G., S.S., W.L. and Z.Z.; Software, Y.G.; Validation, S.S.; Formal analysis, Y.G.; Investigation, Y.G. and J.L.; Data curation, Y.G. and J.L.; Writing—original draft, Y.G.; Writing—review & editing, Q.S.; Supervision, Q.S.; Project administration, Q.S. and Z.Z.; Funding acquisition, Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Education Humanities and Social Sciences Research “Study on the new mechanism of urban green space ecological benefit Measurement and high-quality collaborative development: A case study of Nanjing Metropolitan Area”: grant number 21YJCZH131; the Young elite scientist sponsorship program by the China Association for Science and Technology: grant number YESS20220054; the Social Science Foundation Project of Jiangsu Province: grant number 21GLC002; the National Natural Science Foundation of China: grant number 32101582; the Natural Science Foundation of Jiangsu Province of China: grant number BK20210613; the Natural Science Foundation of the Jiangsu Higher Education Institutions of China: grant number 21KJB220008; the National Natural Science Foundation of China: grant number 32071832. “Qing Lan Project” in Jiangsu Province of China: None. And the APC was funded by Qianqian Sheng.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

Author Ruizhen Yang was employed by the company Nanjing Sky Hunt Data Technology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Diagram of sampling points. (A) is the trees, shrubs, and grasses community; (B) is the trees and shrub community; (C) is the shrub and grasses community; (D) is the trees community; and (E) is the shrub community.
Figure 1. Diagram of sampling points. (A) is the trees, shrubs, and grasses community; (B) is the trees and shrub community; (C) is the shrub and grasses community; (D) is the trees community; and (E) is the shrub community.
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Figure 2. Average dust retention per unit leaf area of plants and different community structure dust retention. (a) is dust retention per unit leaf area of tree. (b) is dust retention per unit leaf area of shrub. (c) is dust retention per unit leaf area of grass. (d) is dust retention per unit leaf area of community structure. a–j represent different levels of significance.
Figure 2. Average dust retention per unit leaf area of plants and different community structure dust retention. (a) is dust retention per unit leaf area of tree. (b) is dust retention per unit leaf area of shrub. (c) is dust retention per unit leaf area of grass. (d) is dust retention per unit leaf area of community structure. a–j represent different levels of significance.
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Figure 3. Plant leaf nitrogen, phosphorus, and potassium content, and standard curve. (a) is nitrogen content of plants. (b) is nitrogen contentration standard curve. (c) is phosphorus content of plants. (d) is phosphorus contentration standard curve. (e) is potassium content of plants. (f) is potassium contentration standard curve. a–h represent different levels of significance.
Figure 3. Plant leaf nitrogen, phosphorus, and potassium content, and standard curve. (a) is nitrogen content of plants. (b) is nitrogen contentration standard curve. (c) is phosphorus content of plants. (d) is phosphorus contentration standard curve. (e) is potassium content of plants. (f) is potassium contentration standard curve. a–h represent different levels of significance.
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Figure 4. Electron micrographs of eight typical plant species. LF: Leaf Thickness; SL: Stomatal Length; SW: Stomatal Width; GWU: Upper Epidermal Groove Width; GWL: Lower Epidermal Groove Width; ST: Stomata; UEP: Upper Epidermis; LEP: Lower Epidermis; TP: Palisade Tissue; STP: Spongy Tissue; CS: Collenchyma Strand; TTR: Transfusion Tissue; X: Xylem; PH: Phloem; TRI: Trichomes. C. deodara is a coniferous plant, and its leaf structure is different from that of broadleaf plants; hence, the leaf annotations are different from those of other broadleaf plants.
Figure 4. Electron micrographs of eight typical plant species. LF: Leaf Thickness; SL: Stomatal Length; SW: Stomatal Width; GWU: Upper Epidermal Groove Width; GWL: Lower Epidermal Groove Width; ST: Stomata; UEP: Upper Epidermis; LEP: Lower Epidermis; TP: Palisade Tissue; STP: Spongy Tissue; CS: Collenchyma Strand; TTR: Transfusion Tissue; X: Xylem; PH: Phloem; TRI: Trichomes. C. deodara is a coniferous plant, and its leaf structure is different from that of broadleaf plants; hence, the leaf annotations are different from those of other broadleaf plants.
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Figure 5. Analysis chart illustrating the correlation between leaf surface microstructure, nitrogen, phosphorus, potassium content, and dust retention ability. LF: Leaf Thickness; SL: Stomatal Length; SW: Stomatal Width; GWU: Upper Epidermal Groove Width; GWL: Lower Epidermal Groove Width; TP: Stomata; WN: Nitrogen Content; WP: Phosphorus Content; WK: Potassium Content; UTSP: Dust Retention per Unit Leaf Area.
Figure 5. Analysis chart illustrating the correlation between leaf surface microstructure, nitrogen, phosphorus, potassium content, and dust retention ability. LF: Leaf Thickness; SL: Stomatal Length; SW: Stomatal Width; GWU: Upper Epidermal Groove Width; GWL: Lower Epidermal Groove Width; TP: Stomata; WN: Nitrogen Content; WP: Phosphorus Content; WK: Potassium Content; UTSP: Dust Retention per Unit Leaf Area.
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Table 1. Plant community species. EDBLM: evergreen deciduous broad-leaved mixed type; MCABL: mixed coniferous and broad-leaved type; EDBLM: evergreen deciduous broad-leaved mixed type; EBL: evergreen broad-leaved type; DBL: deciduous broad-leaved type. “+” is used to connect plants of the same type in the community; “−” is used to connect plants of different types.
Table 1. Plant community species. EDBLM: evergreen deciduous broad-leaved mixed type; MCABL: mixed coniferous and broad-leaved type; EDBLM: evergreen deciduous broad-leaved mixed type; EBL: evergreen broad-leaved type; DBL: deciduous broad-leaved type. “+” is used to connect plants of the same type in the community; “−” is used to connect plants of different types.
Type of Plant Community StructurePlant Structural Community No.The Main Constituent Tree SpeciesPlant Community Growth Types
Tree, shrub, and grass communityA1Camphora camphora + Osmanthus fragrans − Cercis chinensis + Pittosporum Tobira + Photinia × fraseri + Loropetalum chinense − Abelia × grandifloraEDBLM
A2Cedrus deodara + Trachycarpus fortunei − Ligustrum × vicaryi − Ophiopogon japonicusMCABL
A3Ginkgo biloba + Camphora camphora + Osmanthus fragrans − Pittosporum tobira − Cynodon dactylonEDBLM
Tree and shrub community B1Camphora camphora − Ligustrum lucidumEBL
B2Acer palmatum − Photinia × fraseri + Pittosporum tobiraEDBLM
B3Ligustrum lucidum − Rhododendron × pulchrum + Ligustrum quihoui + Photinia × fraseri + Aucuba japonica EDBLM
Shrub and grass communityC1Photinia × fraseri + Rhododendron × pulchrum − Poa annua + Euryops pectinatus+ Ophiopogon japonicusEDBLM
C2Photinia × fraseri − Arrhenatherum elatius EDBLM
Community of treesD1Ligustrum lucidumEBL
D2Platanus acerifoliaDBL
D3Camphora camphoraEBL
Community of shrubsE1Pittosporum tobira + Euonymus japonicusEBL
E2Fatsia japonicaEBL
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Sheng, Q.; Guo, Y.; Lu, J.; Song, S.; Li, W.; Yang, R.; Zhu, Z. A Study on the Dust Retention Effect of the Vegetation Community in Typical Urban Road Green Spaces—In the Case of Ying Tian Street in Nanjing City. Sustainability 2024, 16, 2656. https://doi.org/10.3390/su16072656

AMA Style

Sheng Q, Guo Y, Lu J, Song S, Li W, Yang R, Zhu Z. A Study on the Dust Retention Effect of the Vegetation Community in Typical Urban Road Green Spaces—In the Case of Ying Tian Street in Nanjing City. Sustainability. 2024; 16(7):2656. https://doi.org/10.3390/su16072656

Chicago/Turabian Style

Sheng, Qianqian, Yuanhao Guo, Jiani Lu, Shuang Song, Weizheng Li, Ruizhen Yang, and Zunling Zhu. 2024. "A Study on the Dust Retention Effect of the Vegetation Community in Typical Urban Road Green Spaces—In the Case of Ying Tian Street in Nanjing City" Sustainability 16, no. 7: 2656. https://doi.org/10.3390/su16072656

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