Species-specific efficiency in PM2.5 removal by urban trees: From leaf measurements to improved modeling estimates

Optimizing particulate matter removal through rainfall: Role of duration, intensity, and species in green infrastructure

This study investigates how short-duration intense rainfall events enhance the removal of particulate matter (PM) from plant leaf surfaces in urban environments, thereby contributing to the regulation of air pollution in urban environments and advancing the estimation and measurement of ecosystem services modelling in urban green spaces associated with air pollution regulation and remediation. Using controlled artificial rainfall simulations, we identified optimal combinations of rainfall phase (duration), intensity, plant species, plant height above ground (representing the nozzle-to-leaf distance), and particle diameter to maximize PM removal. Our findings indicate that rainfall phase is crucial in the PM removal process, while particle diameter has minimal influence. Throughout all rainfall phases, plant species consistently play a significant role, driven by differences in leaf morphology and microstructure. The study also identifies optimal rainfall conditions for different species, suggesting dynamic adjustments to intensity and nozzle distance throughout the event to enhance PM removal efficiency. For equal rainfall amounts, lower-intensity, longer-duration events are generally more effective, though nozzle distance should align with species-specific preferences. In contrast, higher rainfall intensities (45-60 mm/h) paired with shorter nozzle distances (1 m plant height, 11 m distance) optimize PM removal for fixed rainfall durations. These findings not only identify optimal rainfall conditions for specific species, providing practical strategies for urban green infrastructure management, but also provide valuable insights into estimating the air purification benefits of rainfall-driven PM removal from leaf surfaces.

Estimating the seasonal and spatial variation of urban vegetation's PM2.5 removal capacity

Fine particulate matter (PM2.5) is one of the most severe factors contributing to urban air pollution, posing significant risks to human health and environmental quality. Urban vegetation, acting as a natural method for pollution mitigation, can effectively reduce harmful air particle concentrations through processes like adsorption and deposition. While much research has quantified urban vegetation's role in PM2.5 removal, the spatial variability and seasonal fluctuations of this process in urban environments remain poorly understood. Furthermore, few studies have quantitatively explored the environmental factors that influence this capability. Using Shanghai as a case study, this research estimates the PM2.5 reduction by urban vegetation in 2022, integrating the i-Tree Eco model with Local Climate Zones (LCZs) classification. The results indicate that vegetation plays a significant role in PM2.5 removal, with a total annual removal of 835 tons and an average removal rate of 0.51 g⋅m-2⋅year-1 per unit leaf area. The maximum annual air quality improvement reached 21.7%, with an average of 4.09%. The removal flux exhibited a clear "double peak" pattern throughout the year, with peaks occurring in late spring and late summer. Significant spatial variations in PM2.5 removal capacity were observed across different LCZs, ranked as follows: Dense Trees > Open Lowrise > Large Lowrise > Bush/Shrub > Scattered Trees > Others. Notably, Open Lowrise areas demonstrated considerable potential in both removal flux and total removal. The 38-42 mm evapotranspiration range was found to be the most effective for PM2.5 removal. However, when evapotranspiration exceeded 50 mm, removal efficiency showed a clear diminishing marginal effect, closely linked to the regulation of leaf stomatal opening and closing. The findings of this study underscore the importance of vegetation in improving air quality and provide valuable insights for urban planning and environmental policy.

Particulate matter and potentially toxic element content in urban ornamental plant species to assess pollutants trapping capacity

Urban environments are usually polluted by anthropogenic activities like traffic, a major source of potentially toxic elements (PTEs), and ornamental plant species may reduce contamination by trapping traffic-related air pollutants in their leaves. The purpose of this study was tested the trapping pollutant capacity of four species commonly used in green areas of Seville city (SW Spain) to better choose species in urban green planning. Composition of particulate matter (PM) obtained from foliar surfaces (sPM) and wax-included (wPM) was determined by EDX-SEM analysis in samples from different city locations. Concentration of different PTEs (Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, V and Zn), by microwave induced-plasma optical emission spectroscopy (MP-AES) were also analyzed in unwashed leaves of one of the selected species (Citrus aurantium) since it is the most cultivated species in Seville. Results showed that Nerium oleander was the plant species which trapped best superficial total and coarse PM. This capacity was enhanced by the presence of a waxy-cuticle and by cuticle thickness but not by leaf hairs. The only species unable to trap fine particles was Bougainvillea glabra. The most representative sPM on leaf surfaces from all species was the largest fraction (59-75%), followed by coarse (25-37%) and fine fractions (2.2-4.4%). In the wax PM, 48% of coarse particles were found in Citrus aurantium. Particulate matter deposited on surface foliage in general did not vary seasonally, while the large fraction of wPM in summer was significantly higher than in winter. The seasonal differences also existed in the level of PTE (Cd, Fe, Ni and V) in leaves. This work indicates that the leaf traits should be taken into account to evaluate the pollutants caption capacity, especially when planning of recreational green urban areas. Particulate matter composition was different according to the pollution sources and mostly contained Al, C, Ca, Fe, K, and Mg, but potentially toxic elements such as Si, As, Cr, Cu and Zn just accounted for 0.11-1.95% of the total elemental content.

Composition and Effects of Aerosol Particles Deposited on Urban Plant Leaves in Terrestrial and Aquatic Habitats

Plants play a vital role in mitigating aerosol particles and improving air quality. This study investigated the composition characteristics and potential effects of particles retained on the leaf surfaces of two amphibious plants (i.e., Alternanthera philoxeroides and Hydrocotyle vulgaris) in both terrestrial and aquatic habitats. The results show that plant habitats influenced the composition of aerosol particles retained on leaf surfaces. Specifically, plants in terrestrial habitats retained a higher mass concentration of coarse and large particles rich in inorganic Ca2+, accounting for over 70% of total ions, whereas plants in aquatic habitats retained a greater abundance of fine and secondary particles with high fractions of water-soluble NO3- and SO42-, taking up over 65% of total anions. Secondary particles deposited on the surfaces of plants in aquatic habitats tend to deliquesce and transform from the particle phase to the liquid phase. Terrestrial habitats facilitate the deposition of large particles. Additionally, particle accumulation on leaf surfaces adversely affected the stomatal conductance of plant leaves, leading to reductions in both the transpiration and photosynthetic rates. This study provides insights into the impact and role of plants from different habitats in mitigating urban particulate pollution.

Time series analysis of PM2.5 pollution risk based on the supply and demand of PM2.5 removal service: a case study of the urban areas of Beijing

Demonstrating the temporal changes in PM2.5 pollution risk in regions facing serious PM2.5 pollution problems can provide scientific evidence for the air pollution control of the region. However, research on the variation of PM2.5 pollution risk on a fine temporal scale is very limited. Therefore, we developed a method for quantitative characterizing PM2.5 pollution risk based on the supply and demand of PM2.5 removal services, analyzed the time series characteristics of PM2.5 pollution risk, and explored the reasons for the temporal changes using the urban areas of Beijing as the case study area. The results show that the PM2.5 pollution risk in the urban areas of Beijing was close between 2008 and 2012, decreased by approximately 16.3% in 2016 compared to 2012, and further decreased by approximately 13.2% in 2021 compared to 2016. The temporal variation pattern of the PM2.5 pollution risk in 2016 and 2021 showed significant differences, including an increase in the number of risk-free days, a decrease in the number of heavily polluted days, and an increase in the stability of the risk day sequence. The significant reduction in risk level was mainly attributed to Beijing's air pollution control measures, supplemented by the impact of COVID-19 control measures in 2021. The results of PM2.5 pollution risk decomposition indicate that compared to the previous 2 years, the stability and predictability of the risk variation in 2016 increased, but the overall characteristics of high risk from November to February and low risk from April to September did not change. The high risk from November to February was mainly due to the demand for coal heating during this period, a decrease in PM2.5 removal service supply caused by plant leaf fall, and the common occurrence of temperature inversions in winter, which hinders the diffusion of air pollutants. This study provides a method for the analysis of PM2.5 pollution risk on fine temporal scales and may provide a reference for the PM2.5 pollution control in the urban areas of Beijing.

Greenspaces And Cardiovascular Health

Accumulating evidence suggests that living in areas of high surrounding greenness or even brief exposures to areas of high greenery is conducive to cardiovascular health, which may be related to the environmental, social, psychological, and physiological benefits of greenspaces. Recent data from multiple cross-sectional, longitudinal, and cohort studies suggest that living in areas of high surrounding greenness is associated with a lower risk of all-cause and cardiovascular mortality. High levels of neighborhood greenery have been linked also to a decrease in the burden of cardiovascular disease risk factors as reflected by lower rates of hypertension, dyslipidemia, and diabetes. Those who live in greener environments report better mental health and more frequent social interactions, which can benefit cardiovascular health as well. In this narrative review, we discuss evidence linking greenspaces to cardiovascular health as well as the potential mechanisms underlying the beneficial effects of greenspaces, including the impact of vegetation on air, noise and light pollution, ambient temperature, physical activity, mental health, and biodiversity. We review literature on the beneficial effects of acute and chronic exposure to nature on cardiovascular disease risk factors, inflammation and immune function, and we highlight the potential cardiovascular effects of biogenic volatile organic compounds that are emitted by trees and shrubs. We identify current knowledge gaps in this area and underscore the need for additional population studies to understand more clearly and precisely the link between greenness and health. Such understanding is urgently needed to fully redeem the promise of greenspaces in preventing adverse environmental exposures, mitigating the effects of climate change, and creating healthier living environments.

Aula Verde (tree room) as a link between art and science to raise public awareness of nature-based solutions

Nature-based solutions inherently require a multifaceted perspective that encompasses diverse fields. The aim of this project is to develop more effective nature-based solutions, climate action and environmental awareness by breaking down boundaries between disciplines and fostering a co-creative process. Concepts of ecology and urban forestry were combined with the research on political ecology, environmental humanities, land art, regenerative art, performing art, participatory art, and more-than-human art. This process resulted in the creation of Aula Verde Aniene. It is located in an urban park in Rome and consists of a stand of trees arranged in circles with a specific design to give the perception of being in an outdoor vegetated room. The project activities involved community participation through art performances and citizen science initiatives. Regulating and cultural ecosystem services of Aula Verde were assessed using i-Tree Eco software and citizens' surveys. Beyond numerical descriptions of ecosystem services, the manuscript introduces shinrin-yoku as a practice to raise awareness of nature. The distinctive approach here described contributed to convey a sense of belonging to the ecosystem to citizens. The project framework and study findings have been developed to formulate policy recommendations and disseminate a format that can be adapted to diverse locations.

The Green Heart Project: Objectives, Design, and Methods

The Green Heart Project is a community-based trial to evaluate the effects of increasing greenery on urban environment and community health. The study was initiated in 2018 in a low-to-middle-income mixed-race residential area of nearly 28,000 residents in Louisville, KY. The 4 square mile area was surveyed for land use, population characteristics, and greenness, and assigned to 8 paired clusters of demographically- and environmentally matched "target" (T) and adjacent "control" (C), clusters. Ambient levels of ultrafine particles, ozone, oxides of nitrogen, and environmental noise were measured in each cluster. Individual-level data were acquired during in-person exams of 735 participants in Wave 1 (2018-2019) and 545 participants in Wave 2 (2021) to evaluate sociodemographic and psychosocial factors. Blood, urine, nail, and hair samples were collected to evaluate standard cardiovascular risk factors, inflammation, stress, and pollutant exposure. Cardiovascular function was assessed by measuring arterial stiffness and flow-mediated dilation. After completion of Wave 2, more than 8,000 mature, mostly evergreen, trees and shrubs were planted in the T clusters in 2022. Post planting environmental and individual-level data were collected during Wave 3 (2022) from 561 participants. We plan to continue following changes in area characteristics and participant health to evaluate the long-term impact of increasing urban greenery.

Particulate matter accumulation by tree foliage is driven by leaf habit types, urbanization- and pollution levels

Particulate matter (PM) pollution poses a significant threat to human health. Greenery, particularly trees, can act as effective filters for PM, reducing associated health risks. Previous studies have indicated that tree traits play a crucial role in determining the amount of PM accumulated on leaves, although findings have often been site-specific. To comprehensively investigate the key factors influencing PM binding to leaves across diverse tree species and geographical locations, we conducted an extensive analysis using data extracted from 57 publications. The data covers 11 countries and 190 tree species from 1996 to 2021. We categorized tree species into functional groups: evergreen conifers, deciduous conifers, deciduous broadleaves, and evergreen broadleaves based on leaf habit and phylogeny. Evergreen conifers exhibited the highest PM accumulation on leaves, and in general, evergreen leaves accumulated more PM compared to deciduous leaves across all PM size classes. Specific leaf traits, such as epicuticular wax, played a significant role. The highest PM loads on leaves were observed in peri-urban areas along the rural-peri-urban-urban gradient. However, the availability of global data was skewed, with most data originating from urban and peri-urban areas, primarily from China and Poland. Among different climate zones, substantial data were only available for warm temperate and cold steppe climate zones. Understanding the problem of PM pollution and the role of greenery in urban environments is crucial for monitoring and controlling PM pollution. Our systematic review of the literature highlights the variation on PM loading among different vegetation types with varying leaf characteristics. Notably, epicuticular wax emerged as a marker trait that exhibited variability across PM size fractions and different vegetation types. In conclusion, this review emphasizes the importance of greenery in mitigation PM pollution. Our findings underscore the significance of tree traits in PM binding. However, lack of data stresses the need for further research and data collection initiatives.

Association of greenness with the disease burden of lower respiratory infections and mediation effects of air pollution and heat: a global ecological study

Exposure to greenness is increasingly linked to beneficial health outcomes, but the associations between greenness and the disease burden of lower respiratory infections (LRIs) are unclear. We used the normalized difference vegetation index (NDVI) and the leaf area index (LAI) to measure greenness and incidence, death, and disability-adjusted life years (DALYs) due to LRIs to represent the disease burden of LRIs. We applied a generalized linear mixed model to evaluate the association between greenness and LRI disease burden and performed a stratified analysis, after adjusting for covariates. Additionally, we assessed the potential mediating effects of fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), and heat on the association between greenness and the disease burden of LRIs. In the adjusted model, one 0.1 unit increase of NDVI and 0.5 increase in LAI were significantly inversely associated with incidence, death, and DALYs due to LRIs, respectively. Greenness was negatively correlated with the disease burden of LRIs across 15-65 age group, both sexes, and low SDI groups. PM2.5, O3, and heat mediated the effects of greenness on the disease burden of LRIs. Greenness was significantly negatively associated with the disease burden of LRIs, possibly by reducing exposure to air pollution and heat.

Spatial Heterogeneity analysis of urban forest ecosystem services in Zhengzhou City

Understanding the spatial distribution of urban forest ecosystem services is essential for urban planners and managers to effectively manage cities and is an essential part of sustainable urban development. Mapping the spatial distribution of urban forest ecosystem services and improving the accuracy of its assessment scale will undoubtedly provide a more accurate reference basis for later management. In this study, we used the i-Tree Eco model and kriging interpolation to quantify and map urban forest ecosystem services and their spatial distribution in Zhengzhou, a city along the lower reaches of the Yellow River in China; analyzed the mapping errors and applicable conditions; and further explored the spatial differences using geographic probes. The i-Tree Eco model estimation results showed that the total carbon storage in the urban forest of Zhengzhou city was 75.7 tons, the annual carbon sequestration was 14.66 tons, the trees and shrubs in the urban area of Zhengzhou city could effectively avoid a total of 307.86 m3 of surface runoff per year, and trees and shrubs removed 411.8 kg/year of air pollution (O3, CO, NO2, PM2.5, PM10, and SO2). The spatial distribution of all urban forest ecosystem services showed significant heterogeneity, but the spatial evaluation precision of different factors varied. GDP and population data showed a negative correlation with ecosystem services, and ecosystem services were abundant in watershed and woodland areas. This study differs from traditional assessments based on regional data due to its improved spatial evaluation accuracy, and the results, discussion, and analysis not only help Zhengzhou's own urban development, but also provide a basis for the future construction and management of other cities, the Central Plains urban agglomeration, and the surrounding larger regions. This will contribute to the enhancement of ecosystem services and thus improve the ecological conditions of the region. This will also have a positive effect on the health of urban residents.

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.