Coagulation effect of aero submicron particles on plant leaves: Measuring methods and potential mechanisms

Selective capture of PM2.5 by urban trees: The role of leaf wax composition and physiological traits in air quality enhancement

Human health risks from particles with a diameter of less than 2.5 µm (PM2.5) highlight the role of urban trees as bio-filters in air pollution control. However, whether the size and composition of particles captured by various tree species differ or not remain unclear. This study investigates how leaf attributes affect the capture of PM2.5, which can penetrate deep into the lungs and pose significant health risks. Using a self-developed particulate matter (PM) resuspension chamber and single-particle aerosol mass spectrometer, we measured the size distribution and mass spectra of particles captured by ten tree species. Notably, Cinnamomum camphora (L.) J.Presl and Osmanthus fragrans Lour. are more effective at capturing particles under 1 µm, which are most harmful because they can reach the alveoli, whereas Ginkgo biloba L. and Platanus × acerifolia (Aiton) Willd. tend to capture larger particles, up to 1.6 µm, which are prone to being trapped in the upper respiratory tract. Leaf physiological traits such as stomatal conductance and water potential significantly enhance the capture of larger particles. The Adaptive Resonance Theory neural network (ART-2a) algorithm classified a large number of single particles to determine their composition. Results indicate distinct inter-species variations in chemical composition of particles captured by leaves. Moreover, we identified how specific leaf wax compositions-beyond the known sticky nature of hydrophobic waxes-contribute to particle adhesion, particularly highlighting the roles of fatty acids and alkanes in adhering particles rich in organic carbon and heavy metals, respectively. This research advances our understanding by linking leaf physiological and wax characteristics to the selective capture of PM2.5, providing actionable insights for urban forestry management. The detailed exploration of particle size and composition, tied to specific tree species, enriches the current literature by quantifying how and why different species contribute variably to air quality improvement. This adds a crucial layer of specificity to the general knowledge that trees serve as bio-filters, offering a refined strategy for planting urban trees based on their particulate capture profiles.

Characterizing leaf-deposited particles: Single-particle mass spectral analysis and comparison with naturally fallen particles

The size and composition of particulate matter (PM) are pivotal in determining its adverse health effects. It is important to understand PM's retention by plants to facilitate its atmospheric removal. However, the distinctions between the size and composition of naturally fallen PM (NFPM) and leaf-deposited PM (LDPM) are not well-documented. Here we utilize a single-particle aerosol mass spectrometer, coupled with a PM resuspension chamber, to analyze these differences. We find that LDPM particles are 6.8-97.3 % larger than NFPM. Employing a neural network algorithm based on adaptive resonance theory, we have identified distinct compositional profiles: NFPM predominantly consists of organic carbon (OC; 31.2 %) and potassium-rich components (19.1 %), whereas LDPM are largely composed of crustal species (53.9-60.6 %). Interestingly, coniferous species retain higher OC content (11.5-13.7 %) compared to broad-leaved species (0.5-1.2 %), while the levoglucosan content exhibit an opposite trend. Our study highlights the active role of tree leaves in modifying PM composition beyond mere passive capture, advocating for a strategic approach to species selection in urban greening initiatives to enhance PM mitigation. These insights provide guidance for urban planners and environmentalists in implementing nature-based solutions to improve urban air quality.

Nature-Inspired Regenerative Fine-Dust-Catching Coatings to Improve Air Quality

Increased particulate matter (PM) concentrations in our ambient air are the cause of various life-threatening diseases and consequently need to be reduced to nonhazardous levels. The natural PM removal capabilities of leaves inspired the development of a low-cost coating technology that exploits natural weather phenomena for its PM catching and removal processes. The herein presented coating is based on microparticle-filled silicone with optimized chemical and physical surface properties. Its surface roughness was tuned using differently sized spray-dried particles, and its surface contact angle was adjusted through silicone tensides, polar ether groups incorporated in the silicon backbone, and the used amount of spray-dried particles. In such a way, optimized silicone coatings showed in laboratory experiments improved catching abilities (>300% relative to glass surfaces), a full retention of adsorbed PM during wind events, and the formation of large PM aggregates. Upon (simulated) rain events, these coatings were regenerated, and the content of harmful PM of various sizes dispersed in water was reduced between ∼73 and 100%. Furthermore, an outdoor test over 100 days showed the functioning of the coating under real-world conditions. These regenerative coatings are readily applicable on diverse surfaces and do not require any further technical infrastructure. Thus, they present an extension of the toolbox for PM reduction technologies.

Uptake and distribution of the inorganic components NH4+ and NO3- in PM2.5 by two Chinese conifers

Plants can effectively purify PM2.5 in the air, thereby improving air quality. Understanding the mechanisms of the uptake and distribution of PM2.5 in plants is crucial for enhancing their ecological benefits. In this study, the uptake and distribution of the water-soluble inorganic compounds ammonium (NH4+) and nitrate (NO3-) ions in PM2.5 by the two native Chinese conifers Manchurian red pine (Pinus tabuliformis) and Bunge's pine (P. bungeana) were investigated using a one-time aerosol treatment method combined with 15N tracing. The results showed the following: (1) Plants can efficiently uptake NH4+ (0.08-0.21 μg/g) and NO3- (0.03-0.68 μg/g) from PM2.5. Manchurian red pine uptakes these compounds more effectively with increases of 2.01-fold for NH4+ and 1.02-fold for NO3- compared with Bunge's pine. (2) The aboveground organs of the plants uptake and distribute more 15N than the belowground organs. The branches had the highest unit mass uptake (0.08-1.60 μg/g) and rate of distribution (16.91-53.60 %) for NH4+, while the leaves had the highest unit mass uptake (0.15-1.18 μg/g) and rate of distribution (50.78-84.88 %) for NO3-. (3) The ability of the aboveground organs to uptake 15N is influenced by the concentration of PM2.5, which showed an overall increase with increasing concentrations with some fluctuations in specific organs. However, the belowground organs were not affected by the concentration of PM2.5. (4) A larger specific leaf area, root-shoot ratio, branch biomass ratio, coarse root biomass ratio, and lower trunk biomass ratio favors the uptake of NH4+ from PM2.5, whereas these traits had a minimal influence on the uptake of NO3-. Manchurian red pine uptaked significantly more NH4+ compared with Bunge's pine, which benefited from the traits described above. These findings further revealed the mechanism of PM2.5 uptake by plants and its relationship with PM2.5 concentration and plant traits, and provided a scientific basis for how to effectively utilize plants to reduce PM2.5 pollution and purify the environment in areas with different pollution concentrations.

Characterizing accumulation and negative effects of aerosol particles on the leaves of urban trees

Urban vegetation can alleviate particulate matter (PM) pollution. Many studies examined the PM retention efficiencies of different plant species, but the PM changes retained on leaf surfaces and their effects on plant leaves have rarely been explored. In this study, two common urban greening tree species of the Yangtze River Delta (i.e., Broussonetia papyrifera and Osmanthus fragrans) were selected to explore the compositions of retained PM and assess their adverse impacts on leaf functional traits. Compared with B. papyrifera, O. fragrans with higher wax content was more efficient in particle accumulation, specifically fine (Φ ≤ 2.5 μm) and coarse (2.5 < Φ ≤ 10 μm) particles. The number density and mass concentration of retained PM on plant leaves tended to increase during the accumulation period. Plant species and accumulation time were two major factors to influence particle retention efficiency. Interestingly, the accumulation of particle retention influenced leaf functional traits, such as photosynthesis rate, stomatal conductance, and transpiration rate. The microscopic observations of PM on leaves confirmed that the toxic components of the retained particles potentially caused leaf injury and stomatal damage. Therefore, the acclimation mechanisms of plants responding to the retained urban aerosols should be paid attention in highly polluted areas.

Coagulation effect of atmospheric submicron particles on plant leaves: Key functional characteristics and a comparison with dry deposition

Submicron particles have become a new focus in research on air pollution control. The abilities of urban tree species to retain particles can be used to alleviate urban haze pollution. However, research has focused mostly on plants and environmental conditions rather than on particle itself. Particle migration and transformation at the leaf-air interface are the key to dust retention. Submicron particles coagulate when they are retained by leaves. In this study, NaCl was used to simulate submicron particles. The average sizes of the particles on the leaves of 10 greening tree species in Shanghai in different seasons were measured using the sweep-resuspension method to characterize the coagulation effect. Thereafter, the effects of leaf characteristics were investigated and analyzed in relation to dry deposition velocity. The results indicated that the particles on the leaves of Ginkgo biloba, Osmanthus fragrans, Sabina chinensis (L.) Ant. "Kaizuca," Cinnamomum camphora, and Metasequoia glyptostroboides were large. The seasonal variability of the sizes of the particles on the leaves of different tree species varied. The average particle size was positively correlated with wax content and negatively correlated with single leaf area; however, the other factors correlated with particle size varied by season. For example, in April, the average particle size was positively correlated with tensile strength, wind resistance, adaxial epidermal roughness, and water potential, whereas the effects of stomatal conductance were more complex. Non-significant correlation was identified between coagulation and dry deposition although both were positively correlated with roughness and wax content. This study explored the effects of leaf characteristics on coagulation. The results may serve as a theoretical foundation for explaining the microscopic process underlying dust retention in plants and may provide a clearer scientific basis for the prevention and control of submicron particle pollution and the selection of urban greening tree species.

Quantitative estimation of the PM2.5 removal capacity and influencing factors of urban green infrastructure

Long-term exposure to PM_2.5 (fine particulate matter with an aerodynamic diameter <2.5 μm) could cause great harm to human health and sustainable development. It remains a challenge to estimate the long-term PM_2.5 removal capacity of nature-based green infrastructure in urban areas. In this paper, the annual PM_2.5 removal capacity of urban green infrastructure (UGI) from 2000 to 2019 in Shenyang was estimated based on the PM2.5 dry deposition model. The spatial heterogeneity of annual PM_2.5 removal capacity were detected Sen-MK test and local spatial autocorrelations analysis. Then the effects of landscape patterns and socioeconomic variables on PM_2.5 removal capacity were explored based on linear regression model. The results illustrated that the PM_2.5 removal capacity of UGI increased significantly from 2000 to 2019 in Shenyang, with the amount of PM_2.5 removal, PM_2.5 removal flux and removal rate increasing by 20.64 Mg/a, 0.0258 g/m²/a, and 0.377 %/a, respectively. The PM_2.5 removal capacity of UGI exhibited spatial heterogeneity in the study area. Specifically, the regions experiencing the increase in PM_2.5 removal capacity of UGI accounted for majority of the old urban area of Shenyang City during the study period; the lower PM_2.5 removal capacity clustered in the center urban area, in which high density impervious surfaces distributed, while the higher PM_2.5 removal capacity mainly gathered in the area with large scale green space; PM_2.5 removal capacity were significantly higher in urban functional zones with a high proportion of green spaces. The landscape metrics representing fragmentation and shape complexity positively affected the annual PM_2.5 removal flux and removal rate, while the aggregation metrics had significantly negative correlations with the PM_2.5 removal flux and removal rate. Moreover, it was also found that population density and GDP negatively affected the PM_2.5 removal capacity of UGI. This study provides a methodological reference and some new insights for future urban landscape planning and air pollution purification.

Particulate matter resuspension from simulated urban green floors using a wind tunnel-mounted closed chamber

Background

Green areas are thought to reduce particulate matter (PM) concentrations in urban environments. Plants are the key to PM reduction via various mechanisms, although most mechanisms do not lead to the complete removal of PM. Ultimately, PM falls into the soil via wind and rainfall. However, the fallen PM can re-entrain the atmosphere, which can affect plants capacity to reduce PM. In this study, we simulated an urban green floor and measured the resuspension of PM from the surface using a new experimental system, a wind tunnel-mounted closed chamber.

Methods

The developed system is capable of quantifying the resuspension rate at the millimeter scale, which is measured by using the 1 mm node chain. This is adequate for simulating in situ green floors, including fallen branches and leaves. This addressed limitations from previous studies which focused on micrometer-scale surfaces. In this study, the surfaces consisted of three types: bare sand soil, broadleaves, and coniferous leaves. The resuspended PM was measured using a light-scattering dust detector.

Results

The resuspension rate was highest of 14.45×10^-4 s^-1 on broad-leaved surfaces and lowest on coniferous surfaces of 5.35×10^-4 s^-1 (p < 0.05) and was not proportional to the millimeter-scale surface roughness measured by the roller chain method. This might be due to the lower roughness density of the broad-leaved surface, which can cause more turbulence for PM resuspension. Moreover, the size distribution of the resuspended PM indicated that the particles tended to agglomerate at 2.5 µm after resuspension.

Conclusion

Our findings suggest that the management of fallen leaves on the urban green floor is important in controlling PM concentrations and that the coniferous floor is more effective than the broadleaved floor in reducing PM resuspension. Future studies using the new system can be expanded to derive PM management strategies by diversifying the PM types, surfaces, and atmospheric conditions.

A high-resolution study of PM2.5 accumulation inside leaves in leaf stomata compared with non-stomatal areas using three-dimensional X-ray microscopy

Plant leaves retain atmospheric particulate matter (PM) on their surfaces, helping PM removal and risk reduction of respiratory tract infection. Several processes (deposition, resuspension, rainfall removal) can influence the PM accumulation on leaves and different leaf microstructures (e.g., trichomes, epicuticular waxes) can also be involved in retaining PM. However, the accumulation and distribution of PM on leaves, particularly at the stomata, are unclear, and the lack of characterization methods limits our understanding of this process. Thus, in this study, we aimed to explore the pathway through which PM_2.5 (aerodynamic diameter ≤ 2.5 μm) enters plant leaves, and the penetration depth of PM_2.5 along the entry route. Here, an indoor experiment using diamond powder as a tracer to simulate PM_2.5 deposition on leaves was carried out. Then, the treated and non-treated leaves were scanned by using three-dimensional (3D) X-ray microscopy. Next, the grayscale value of the scanned images was used to compare PM_2.5 accumulation in stomatal and non-stomatal areas of the treated and non-treated leaves, respectively. Finally, a total PM_2.5 volume from the abaxial epidermis was calculated. The results showed that, first, a large amount of PM_2.5 accumulates within leaf stomata, whereas PM_2.5 does not accumulate at non-stomatal areas. Then, the penetration depth of PM_2.5 in stomata of most tree species was 5-14 μm from the abaxial epidermis. For the first time, 3D X-ray microscope scanning was used to confirm that a pathway by which PM_2.5 enters the leaves is through the stomata, which is fundamental for further research on how PM_2.5 translocates and interacts with tissues and cells in leaves.

Quantifying the capacity of tree branches for retaining airborne submicron particles

Human health risks brought by fine atmospheric particles raise scholarly and policy awareness about the role of urban trees as bio-filters of air pollution. While a large number of empirical studies have focused on the characteristics of vegetation leaves and their effects on atmospheric particle retention, the dry deposition of particles on branches, which plays a significant role in capturing and retaining particles during the defoliation period and contributes substantially to total removal of atmospheric particles, is under-investigated. To fill in this knowledge gap, this case study examined the dry deposition velocities (V_d) of submicron particulate matters (PM₁) on the branches of six common deciduous species in Shanghai (China) using laboratory experiments. And the association between V_d and key branch anatomical traits (including surface roughness, perimeter, rind width proportion, lenticel density, peeling, and groove/ridge characteristics) was explored. It was found that surface roughness would increase V_d, as a rougher surface significantly increases turbulence, which is conducive to particle diffusion. By contrast, peeling, branch perimeter, and lenticel density would decrease V_d. Peeling represents the exfoliated remains on the branch surfaces which may flutter considerably with airflow, leading to particle resuspension and low V_d. When branch perimeter increases, the boundary layer of branches thickens and a wake area appears, increasing the difficulty of particles to reach branch surface, and reducing V_d. While lenticels can increase the roughness of branch surface, their pointy shape would uplift airflow and cause a leeward wake area, lowering V_d. This finely wrought study contributes to a better understanding of branch dry deposition during leaf-off seasons and potential of deciduous trees serving as nature-based air filters all year round in urban environments.

Analysis of the influencing factors of atmospheric particulate matter accumulation on coniferous species: measurement methods, pollution level, and leaf traits

Urban trees, especially their leaves, have the potential to capture atmospheric particulate matter (PM) and improve air quality. However, the amount of PM deposited on leaf surfaces detected by different methods varies greatly, and quantitative understanding of the relationship between PM retention capacity and various microstructures of leaf surfaces is still limited. In this study, three measurement methods, including the leaf washing (LW) method, aerosol regeneration (AR) method, and scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDX) method, were used to determine the PM retention capacity of leaf surfaces of three coniferous species. Additionally, we analyzed the leaf traits and elemental composition of PM on leaves collected from different sites. The results showed that Pinus tabulaeformis and Abies holophylla were more efficient species in capturing PM than Juniperus chinensis, but different measurement methods could affect the detected results of PM accumulation on leaf surfaces. The concentrations of trace elements accumulated on leaf surfaces differed considerably between different sites. The greatest accumulation of elements that occurred on the leaf surface was at the Shenfu Highway site exposed to high PM pollution levels and the smallest accumulation at the Dongling park site. The stomatal density and contact angle were highly correlated with the PM retention capacity of leaf surfaces of the tested species (Pearson coefficient: r = 0.87, p < 0.01 and r =  - 0.70, p < 0.05), while the roughness and groove width were not significantly correlated (Pearson coefficient: r = 0.16 and r =  - 0.03). This study suggests that a methodological standardization for measuring PM is urgently required and this could contribute to selecting greening tree species with high air purification capacity.

Individual effects of trichomes and leaf morphology on PM2.5 dry deposition velocity: A variable-control approach using species from the same family or genus

Urban green infrastructure is closely linked to the alleviation of pollution from atmospheric particulate matter. Although particle deposition has been shown to depend on leaf characteristics, the findings from earlier studies are sometimes ambiguous due to the lack of controlling variables. In this study, we investigated the impact of leaf morphological characteristics on PM_2.5 dry deposition velocity by employing a control-variable approach. We focused on four indices: trichome density, petiole length, aspect ratio (width-to-length ratio), and fractal deviation. For each index, tree species were chosen from the same family or genus to minimize the influence of other factors and make a group of treatments for an individual index. The dry deposition velocities of PM_2.5 were determined through application of an indirect method. The results revealed that the presence of leaf trichomes had a positive effect on PM_2.5 dry deposition velocity, and a higher trichome density also led to a greater particle deposition velocity. Lower leaf aspect ratio, shorter petioles, and higher leaf fractal deviation were associated with greater PM_2.5 dry deposition velocity. The control-variable approach allows to investigate the correlation between deposition velocity and a certain leaf characteristic independently while minimizing the effects of others. Thus, our study can clarify how a single leaf characteristic affects particle deposition velocity, and expound its potential mechanism more scientifically than the published studies. Our research points out the importance of controlling variables, and also provides ideas for future researches on related factors to be found. Meanwhile the results would help provide insight into design improvements or adaptive management for the alleviation of air pollution.

Effects of the leaf functional traits of coniferous and broadleaved trees in subtropical monsoon regions on PM2.5 dry deposition velocities

Plants can intercept airborne particulate matter through deposition. Different types of plants exhibit different functional leaf traits, which can affect the dry deposition velocity (V_d). However, the most crucial leaf traits of coniferous and broadleaved trees remain unidentified. In this study, we selected 18 typical plants from the subtropical monsoon regions, where PM_2.5 (fine particulate matter with a diameter of ≤2.5 μm) concentrations are relatively high, and classified them into coniferous and broadleaved categories. Subsequently, we analyzed the relationships between V_d and leaf surface free energy (SFE), single leaf area (LA_s), surface roughness (SR), specific leaf area (SLA), epicuticular wax content (EWC), and width-to-length ratio (W/L). The results indicated that most coniferous trees exhibited a high V_d. The correlation analysis revealed that SFE, SR, LA_s, and W/L were the key factors that affected the V_d of all the tested species. SFE and SLA had the strongest influence on the V_d of broadleaved trees, whereas LA_s and SLA had the strongest effect on that of coniferous trees. Most coniferous trees had a high SLA, which can reduce water loss and hinder particle deposition. However, the stiff leaves of coniferous trees fluttered less, resulting in a larger leaf area that enhanced the capture efficiency. The leaf structure of broadleaved trees is more flexible, resulting in erratic flutter, which may impede deposition and lead to high resuspension. Coniferous and broadleaved trees may have different dominant leaf traits that affect particle deposition.