Improving local air quality in cities: to tree or not to tree?

Air pollution and climate change as grand challenges to sustainability

There is a cross-disciplinary link between air pollution, climate crisis, and sustainable lifestyle as they are the most complex struggles of the present century. This review takes an in-depth look at this relationship, considering carbon dioxide emissions primarily from the burning of fossil fuels as the main contributor to global warming and focusing on primary SLCPs such as methane and ground-level ozone. Such pollutants severely alter the climate through the generation of greenhouse gases. The discussion is extensive and includes best practices from conventional pollution control technologies to hi-tech alternatives, including electric vehicles, the use of renewables, and green decentralized solutions. It also addresses policy matters, such as imposing stricter emissions standards, setting stronger environmental regulations, and rethinking some economic measures. Besides that, new developments such as congestion charges, air ionization, solar-assisted cleaning systems, and photocatalytic materials are among the products discussed. These strategies differ in relation to the local conditions and therefore exhibit a varying effectiveness level, but they remain evident as a tool of pollution deterrence. This stresses the importance of holistic and inclusive approach in terms of engineering, policies, stakeholders, and ecological spheres to tackle.

Impact of single and combined local air pollution mitigation measures in an urban environment

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

Associations between community green view index and fine particulate matter from Airboxes

Urban greenery can help to improve air quality, reduce health risks and create healthy livable urban communities. This study aimed to explore the role of urban greenery in reducing air pollution at the community level in Tainan City, Taiwan, using air quality sensors and street-view imagery. We also collected the number of road trees around each air quality sensor site and identified the species that were best at absorbing PM2.5. Three greenness metrics were used to assess community greenery in this study: two Normalized Difference Vegetation Indices (NDVI) from different satellites and the Green View Index (GVI) from Google Street View (GSV) images. Land-use Regression (LUR) was used for statistical analysis. The results showed that a higher GVI within a 500 m buffer was significantly associated with decreased PM2.5. Neither NDVI metrics within a 500 m circular buffer were significantly associated with decreased PM2.5. Evergreen trees were significantly associated with lower ambient PM2.5, compared with deciduous and semi-deciduous trees. Because localized changes in air quality profoundly affect public health and environmental equity, our findings provide evidence for future urban community greenspace planning and its beneficial impacts on reducing air pollution.

A comprehensive review of urban vegetation as a Nature-based Solution for sustainable management of particulate matter in ambient air

Air pollution is one of the most pressing environmental threats worldwide, resulting in several health issues such as cardiovascular and respiratory disorders, as well as premature mortality. The harmful effects of air pollution are particularly concerning in urban areas, where mismanaged anthropogenic activities, such as growth in the global population, increase in the number of vehicles, and industrial activities, have led to an increase in the concentration of pollutants in the ambient air. Among air pollutants, particulate matter is responsible for most adverse impacts. Several techniques have been implemented to reduce particulate matter concentrations in the ambient air. However, despite all the threats and awareness, efforts to improve air quality remain inadequate. In recent years, urban vegetation has emerged as an efficient Nature-based Solution for managing environmental air pollution due to its ability to filter air, thereby reducing the atmospheric concentrations of particulate matter. This review characterizes the various mitigation mechanisms for particulate matter by urban vegetation (deposition, dispersion, and modification) and identifies key areas for further improvements within each mechanism. Through a systematic assessment of existing literature, this review also highlights the existing gaps in the present literature that need to be addressed to maximize the utility of urban vegetation in reducing particulate matter levels. In conclusion, the review emphasizes the urgent need for proper air pollution management through urban vegetation by integrating different fields, multiple stakeholders, and policymakers to support better implementation.

Uneven PM2.5 dispersion pattern across an open-road vegetation barrier: Effects of planting combination and wind condition

The increased traffic-induced emissions contribute to the exacerbation of airborne particulate matter (PM) pollution. The vegetation barrier (VB) provides a means of reducing the traffic-induced pollutants. However, the effects of VB configuration and local environment on PM dispersion and reduction remain unclear, and thereby needs further advancement on VB design and characteristics. This study constructed a 3D numerical model based on field survey in an open-road VB of Shanghai urban area, and then simulated PM2.5 dispersion under various VB configurations and wind conditions. The results consolidated that the presence of the VB reduced PM2.5 concentration by over 15 % across the VB. A greater bush coverage (2/3 and more) reduces over 14 % more PM2.5 pollution across the VB than that for a greater arbor coverage, and reduces 6 % more PM2.5 pollution in the sidewalk canyon. Given a certain bush planting coverage, planting bushes in the windward area is beneficial to the overall PM2.5 reduction by approximately 4-14 %. The wind directions determine the overall pattern of PM2.5 dispersion across the VB plot, decreasing trends for perpendicular winds but fluctuating curves for parallel winds Wind velocities largely contribute to the changing rates of PM2.5 concentration, the increased wind speed from 1 m/s to 7 m/s accumulated 5-11 % more PM2.5 pollution across the VB plot. This study provides practical insights for effective VB designs in order to mitigate the PM pollution and the human's exposure to PM2.5 in urban open-road environments.

Reassessing the role of urban green space in air pollution control

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

Environmental Injustice, Tree Canopy Cover, and Academic Proficiency at Utah Public Primary Schools

Background

Tree canopy cover has mental and physical health benefits for children, yet distributional environmental injustices in tree canopy cover near schools are rarely investigated. Some evidence suggests that tree canopy coverage positively influences aggregated school-level children's academic proficiency metrics. There is a lack of research if canopy cover moderates the negative effect of particulate matter on academic proficiency.

Methods

We linked data on schools from the National Center for Education Statistics, Utah's Student Assessment of Growth and Excellence, the National Land Cover Database, and the U.S. Environmental Protection Agency. We used generalized estimating equations, which account for non-normally distributed data and clustering, to analyze data from the 2015 to 2016 school year.

Results

Greater school social disadvantage (higher percentages of students qualifying for free/reduced price meals and higher percentages of racial/ethnic minority students) was significantly associated with reductions in tree canopy cover within 1000 m and 500 m of the school. Greater tree canopy coverage at 1000 m and 500 m was significantly associated with a lower percentage of students testing below proficient on year-end math and language arts exams. Additional days of peak fine particulate matter were associated with higher percentages of students testing below proficient in math.

Discussion

Socially disadvantaged primary schools in Utah were surrounded by less canopy cover. There was a protective effect of tree canopy cover on academic proficiency in math and language arts.

Conclusion

Findings suggest targeting carefully designed tree planting efforts at socially disadvantaged schools and testing interventions involving tree planting and changes in academic proficiency.

Land-Use Decisions Have Substantial Air Quality Health Effects

Understanding how best to use limited land without compromising food security, health, and beneficial ecosystem functions is a critical challenge of our time. Ecosystem service assessments increasingly inform land-use decisions but seldom include the effects of land use on air quality, the largest environmental health risk. Here, we estimate and value the air quality health effects of potential land-use policies and projected trends in the United States, alongside carbon sequestration and economic returns to land, until 2051. We show that air quality health effects are of first-order importance in land-use decisions, often larger in value than carbon sequestration and economic returns combined. When air quality is properly accounted for, policies that appeared beneficial are shown to be detrimental and vice versa. Land-use-driven air quality impacts are largely from agricultural emissions and biogenic forest emissions, although incentives for reduced deforestation remain beneficial overall. Without evaluating air quality, we are unable to determine whether land-use decisions make us better or worse off.

The influence of plant species, leaf morphology, height and season on PM capture efficiency in living wall systems

Green infrastructure (GI) is already known to be a suitable way to enhance air quality in urban environments. Living wall systems (LWS) can be implemented in locations where other forms of GI, such as trees or hedges, are not suitable. However, much debate remains about the variables that influence their particulate matter (PM) accumulation efficiency. This study attempts to clarify which plant species are relatively the most efficient in capturing PM and which traits are decisive when it comes to the implementation of a LWS. We investigated 11 plant species commonly used on living walls, located close to train tracks and roads. PM accumulation on leaves was quantified by magnetic analysis (Saturation Isothermal Remanent Magnetization (SIRM)). Several leaf morphological variables that could potentially influence PM capture were assessed, as well as the Wall Leaf Area Index. A wide range in SIRM values (2.74-417 μA) was found between all species. Differences in SIRM could be attributed to one of the morphological parameters, namely SLA (specific leaf area). This suggest that by just assessing SLA, one can estimate the PM capture efficiency of a plant species, which is extremely interesting for urban greeners. Regarding temporal variation, some species accumulated PM over the growing season, while others actually decreased in PM levels. This decrease can be attributed to rapid leaf expansion and variations in meteorology. Correct assessment of leaf age is important here; we suggest individual labeling of leaves for further studies. Highest SIRM values were found close to ground level. This suggests that, when traffic is the main pollution source, it is most effective when LWS are applied at ground level. We conclude that LWS can act as local sinks for PM, provided that species are selected correctly and systems are applied according to the state of the art.

Efficacy of green infrastructure in reducing exposure to local, traffic-related sources of airborne particulate matter (PM)

One aim of roadside green infrastructure (GI) is to mitigate exposure to local, traffic-generated pollutants. Here, we determine the efficacy of roadside GI in improving local air quality through the deposition and/or dispersion of airborne particulate matter (PM). PM was collected on both pumped air filters and on the leaves of a recently installed 'tredge' (trees managed as a head-high hedge) at an open road environment next to a primary school in Manchester, U.K. The magnetic properties of PM deposited on leaves and filters (size fractions PM10 and PM2.5) were deduced from hysteresis loops, first-order reversal curves (FORCs), and low-temperature remanence measurements. These were complemented with electron microscopy to identify changes in magnetic PM concentration downwind of the tredge/GI. We show that the tredge is permeable to airflow using a simple CO2 tracer experiment; hence, it allows interception and subsequent deposition of PM on its leaves. Magnetic loadings per m3 of air from filters (PM10 saturation magnetisation, Ms, at 5 K) were reduced by 40 % behind the tredge and a further 63 % in the playground; a total reduction of 78 % compared to roadside air. For the PM2.5 fraction, the reduction in magnetic loading behind the tredge was remarkable (82 %), reflecting efficient diffusional capture of sub-5 nm Fe-oxide particles by the tredge. Some direct mixing of roadside and playground air occurs at the back of the playground, caused by air flow over, and/or through gaps in, the slowly-permeable tredge. The magnetic loading on tredge leaves increased over successive days, capturing ~23 % of local, traffic-derived PM10. Using a heuristic two-dimensional turbulent mixing model, we assess the limited dispersion of PM < 22.5 μm induced by eddies in the tredge wake. This study demonstrates that PM deposition on leaves reduces exposure significantly in this school playground setting; hence, providing a cost-effective mitigation strategy.

Dry deposition effect of urban green spaces on ambient particulate matter pollution in China

Particulate matter (PM) is a major source of urban air pollution that poses a serious threat to the environment and human health. This study quantified the dry deposition effect of PM2.5 and PM10 on vegetation using a mathematical model to overcome the limitations of traditional site-scale research. Additionally, multi-source satellite remote sensing products were combined to form a raster dataset to estimate the effect of dry deposition on PM2.5 and PM10 in China's urban green spaces from 2000 to 2020. The spatial and temporal changes in the long-term series were analyzed, and the influence of environmental factors on dry deposition was analyzed in combination with wavelet changes. The experimental results showed that: 1) from 2000 to 2020, the dry deposition effect of PM2.5 and PM10 on vegetation showed an initial increasing and then decreasing trend caused by the sudden drop in atmospheric pollutant particle concentration driven by local policies; 2) broad-leaved forests provided the main dry deposition effects in urban spaces, accounting for 89.22 %, indicating a need to increase the density of these forest types in urban development planning to improve air quality; and 3) PM2.5, PM10, and environmental impact factors have time-frequency scale coherences, and the coherence between PM2.5 reduction and these factors is more complex than that of PM10, with precipitation being the best variable to explain the change in PM2.5 and PM10. These findings are important for the prevention and control of urban air pollution, regional planning of green spaces, and sustainable development of cities.

Prevention of "bygone futures" due to road traffic injuries in children

Road traffic injuries remain one of the common and leading causes of death among children and adolescents till the age of 19 years. Road safety is important for children since their physical activity, active travel, independence and development are largely affected by it. Solutions for road safety with benefits for people as well as an economy exist which should be implemented effectively and efficiently. These solutions which combine engineering, legislation and behavioural interventions should be implemented in an integrated Safe Systems Approach. The future of the children must be safeguarded from these injuries and every effort towards it being converted into "bygone figures" must be done diligently and honestly. The various risk factors and interventions possibly explained in this review article shall help in better understanding of the causes and possible guidelines at a policy level to prevent road traffic injuries in children.

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.

Environmental impacts of air pollution and its abatement by plant species: A comprehensive review

Air pollution is one of the major global environmental issues urgently needed attention for its control through sustainable approaches. The release of air pollutants from various anthropogenic and natural processes imposes serious threats to the environment and human health. The green belt development using air pollution-tolerant plant species has become popular approach for air pollution remediation. Plants' biochemical and physiological attributes, especially relative water content, pH, ascorbic acid, and total chlorophyll content, are taken into account for assessing air pollution tolerance index (APTI). In contrast, anticipated performance index (API) is assessed based on socio-economic characteristics including "canopy structure, type, habit, laminar structure, economic value and APTI score" of plant species. Based on previous work, plants with high dust-capturing capacity are identified in Ficus benghalensis L. (0.95 to 7.58 mg/cm2), and highest overall PM accumulation capacity was observed in Ulmus pumila L. (PM10 = 72 µg/cm2 and PM2.5 = 70 µg/cm2) in the study from different regions. According to APTI, the plant species such as M. indica (11 to 29), Alstonia scholaris (L.) R. Br. (6 to 24), and F. benghalensis (17 to 26) have been widely reported as high air pollution-tolerant species and good to best performer in terms of API at different study sites. Statistically, previous studies show that ascorbic acid (R2 = 0.90) has good correlation with APTI among all the parameters. The plant species with high pollution tolerance capacity can be recommended for future plantation and green belt development.

Impact of trees on gas concentrations and condensables in a 2-D street canyon using CFD coupled to chemistry modeling

Trees grown in streets impact air quality by influencing ventilation (aerodynamic effects), pollutant deposition (dry deposition on vegetation surfaces), and atmospheric chemistry (emissions of biogenic volatile organic compounds, BVOCs). To qualitatively evaluate the impact of trees on pollutant concentrations and assist decision-making for the greening of cities, 2-D simulations on a street in greater Paris were performed using a computational fluid dynamics tool coupled to a gaseous chemistry module. Globally, the presence of trees has a negative effect on the traffic-emitted pollutant concentrations, such as NO₂ and organic condensables, particularly on the leeward side of a street. When not under low wind conditions, the impact of BVOC emissions on the formation of most condensables within the street was low owing to the short characteristic time of dispersion compared with the atmospheric chemistry. However, autoxidation of BVOC quickly forms some extremely-low volatile organic compounds, potentially leading to the formation of ultra-fine particles. Planting trees in streets with traffic is only effective in mitigating the concentration of some oxidants such as ozone (O₃), which has low levels in cities regardless of this, and hydroxyl radical (OH), which may slightly lower the rate of oxidation reactions and the formation of secondary species in the street.

Effects of Green Network Management of Urban Street Trees on Airborne Particulate Matter (PM2.5) Concentration

Street trees are crucial for air pollutant reduction in urban areas. Herein, we used computational fluid dynamics (CFD) simulation to identify changes in airborne particulate matter (PM_2.5) concentration based on wind characteristics (direction and velocity) and the green network of street trees. The green network was assessed based on composition of the green area of street trees in the central reserve area and between the motor and pedestrian roads. The PM_2.5 concentration varied according to the presence or absence of major reserve planting and the planting structure of the street trees, but not according to the wind direction or velocity. The concentration was lower when the wind direction was 45° (than when the wind direction was 0°), whereas it showed a more significant decrease as the wind velocity increased. Despite variation at each measurement site, the PM_2.5 reduction was generally higher when the central reserve and street trees had a multi-planting structure. Hence, to ensure an effective reduction in the PM_2.5 concentration on motor roads and reduce its negative impact on pedestrians, both arbors and shrubs should be planted in the central reserve area. The study results will serve as reference for managing the green area network and linear green infrastructure in terms of improving the atmospheric environment.

Determination of optimal height of barriers to reduce the amount of pollution in the viaduct settings in an idealized urban canyon: a numerical study

In this work, we numerically investigate the process of atmospheric air pollution in idealized urban canyons along the road in the presence of a viaduct, taking into account different height of barriers. To solve this problem, the 3D Reynolds-averaged Navier-Stokes equations (RANS) were used. The closure of this system of equations was achieved by using various turbulent models. The verification of the mathematical model and the numerical algorithm was carried out using a test problem. The obtained results using various turbulent models were compared with experimental data and calculated results of other authors. The main problem considered in this work is characterized as follows: assessment of emissions of pollutants between buildings using barriers of various types in the presence of a viaduct. Computational results have shown that the barrier viaduct plays a large role in improving air quality in urban canyons. So, for example, a barrier erected on a viaduct with a height of 2 m reduces the concentration value to a cross-section x = 84 by more than 2 times in comparison with the case of a complete absence of protective barriers. A similar situation was observed with barriers erected above the earth's surface: located along the road, they also significantly reduce the value of the concentration of pollutants. Thus, the presence of barriers in both cases is necessary to prevent the dispersion and deposition of pollutants.

How Nature Benefits Mental Health

Abstract. We present an overview of the evidence of how nature benefits mental health, popular theories used to explain the effects, and the development potential of these theories. A large body of evidence highlights the beneficial effects of nature on mental health, with observed outcomes ranging from alleviating the symptoms of psychiatric disorders to improvements in cognitive abilities. The theoretical backbone for these salutary effects of nature consists of a set of models, mainly the attention restoration theory (ART), the stress reduction theory (SRT), and the Biophilia hypothesis. However, these high-level models are only loosely related and lack a pronounced biopsychological basis. While biopsychological measurements have been used widely in recent years, these efforts have not sufficiently been reflected in theories aiming to explain the benefits of nature contact for mental health. This paper seeks to encourage interdisciplinary work and further theory development to guide both research and practice toward strategically green and healthy living conditions.

Do plant traits help to design green walls for urban air pollution control? A short review of scientific evidences and knowledge gaps

It is often claimed that green walls (GW) and living wall systems (LWS) have a positive effect on urban air pollution problems if their plants composition is optimal (design of the LWS). An in-depth review of the knowledge on plants traits maximizing GW effects on air pollution shows that these might be hasty conclusions: there are still some important knowledge gaps. Robust conclusions can only be drawn for particulate matter (PM): the other pollutants are not analyzed by a sufficient number of studies. It can be concluded that leaves with hairs/trichomes are the most effective to capture PM. The rougher and the smaller the leaf is, the more PM it catches. The analysis of the plant composition of six LWS in Belgium indicated that these LWS supported a plant community dominated by only a few species, which do not exhibit in majority the most effective traits to maximize their PM capture. Regarding climbing plants, only three out of seven commonly used creepers in Belgium present hairs/trichomes on their leaves. Studies conducted on other pollutants and other traits are required to optimize the GW plant composition and to maximize their effects on air quality.

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

The growing population in cities is causing a deterioration of air quality due to the emission of pollutants, causing serious health impacts. Trees and urban forests can contribute through the interception and removal of air pollutants such as particulate matter (PM). The dry deposition of PM by vegetation depends on air pollutant concentration, meteorological conditions, and specific leaf traits. Several studies explored the ability of different plant species to accumulate PM on leaf structures leading to the development of models to quantify the PM removal. The i-Tree Eco is the most used model to evaluate ecosystem services provided by urban trees. However, fine particulate matter (PM_2.5) removal is still calculated with a poorly evaluated function of deposition velocity (which depends on wind speed and leaf area) without differentiating between tree species. Therefore, we present an improvement of the standard model calculation introducing a leaf trait index to distinguish the species effect on PM net removal. We also compared model results with measurements of deposited leaf PM by vacuum filtration. The index includes the effect of morphological and functional leaf characteristics of tree species using four parameters: leaf water storage, deposition velocity, resuspension rate and leaf washing capacity. Leaves of 11 common urban tree species were sampled in representative areas of the city of Ferrara (Italy) and at different times of the year from 2018 to 2021. This includes four deciduous broadleaf trees (Tilia cordata, Platanus acerifolia, Acer platanoides, Celtis australis), three evergreen broadleaf trees (Quercus ilex, Magnolia grandiflora, Nerium oleander), and four conifers (Thuja orientalis, Cedrus libani, Pinus pinaster, Picea abies). The results provide significant advancement in assessing PM removal using decision support tools such as models to properly select tree species for future urban tree planting programs aimed at improving air quality.

Numerical simulation of the influence of building-tree arrangements on wind velocity and PM2.5 dispersion in urban communities

Airflow behavior and outdoor PM_2.5 dispersion depend significantly on the building-tree layouts and orientation towards the prevailing wind conditions. To investigate this issue, the present work evaluates the aerodynamic effect of different building-tree layouts on the outdoor PM_2.5 dispersions in the urban communities of Shijiazhuang City, China. The adopted numerical CFD technique was based on the standard k-ε model and the Disperse Phase Model (DPM). For this study, ten different building-tree arrangements were conceptualized and all these configurations were simulated by using Ansys Fluent software to quantify the implications on the outdoor PM_2.5 dispersion due to their presence. The results have shown that: (1) a wide building interval space could benefit the air ventilation and thus decrease PM_2.5 concentrations, however, this effectiveness is highly influenced by the presence of the trees; (2) the trees on the leeward side of a building tend to increase the local wind velocity and decrease the pedestrian-level PM_2.5 concentrations, while those on the windward side tend to decrease the wind velocity. The small distance with trees in the central space of the community forms a wind shelter, hindering the particle dispersion; and (3) the configuration of parallel type buildings with clustered tree layouts in the narrow central space is most unfavorable to the air ventilation, leading to larger areas affected by excessive PM_2.5 concentration.

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.

Protecting playgrounds: local-scale reduction of airborne particulate matter concentrations through particulate deposition on roadside ‘tredges’ (green infrastructure)

Exposure to traffic-related particulate air pollution has been linked with excess risks for a range of cardiovascular, respiratory and neurological health outcomes; risks likely to be exacerbated in young children attending schools adjacent to highly-trafficked roads. One immediate way of reducing airborne PM concentrations at the local (i.e., near-road community) scale is installation of roadside vegetation as a means of passive pollution abatement. Roadside vegetation can decrease airborne PM concentrations, through PM deposition on leaves, but can also increase them, by impeding airflow and PM dispersion. Critical to optimizing PM removal is selection of species with high particle deposition velocity (Vd) values, currently under-parameterised in most modelling studies. Here, the measured amounts of leaf-deposited magnetic PM after roadside greening (‘tredge’) installation, and measured reductions in playground PM, particle number and black carbon concentrations demonstrate that air quality improvements by deposition can be achieved at the local, near-road, community/playground scale. PM deposition on the western red cedar tredge removed ~ 49% of BC, and ~ 46% and 26% of the traffic-sourced PM_2.5 and PM₁, respectively. These findings demonstrate that roadside vegetation can be designed, installed and maintained to achieve rapid, significant, cost-effective improvement of air quality by optimising PM deposition on plant leaves.

Urban afforestation: using phytotoxicity endpoints to compare air pollution tolerance of two native Brazilian plants Aroeira (Schinus terebinthifolius) and Cuvatã (Cupania vernalis)

Urban afforestation can mitigate the effects of air pollution, but the suitability of plant species for this purpose needs to be determined according to pollution intensity and climate change. The goal of this study was to evaluate the sensitivity of different phytotoxicity endpoints using two native Brazilian plant species as models, Aroeira (Schinus terebinthifolius) and Cuvatã (Cupania vernalis). The sensitivity parameters evaluated could help in selecting the most air-pollution-tolerant plant species for use in urban afforestation programs. The two plant species were exposed, in a greenhouse, to the combustion gases of a diesel engine for 120 days, with daily intermittent gas exposure. Every 30 days, leaf injury (chlorosis and necrosis), biomass, and physiological/biochemical parameters (proteins, chlorophyll, and peroxidase enzyme activity) were evaluated for both plant species. For the two selected species, the endpoints studied can be ranked according to their sensitivity (or inversely the tolerance) to diesel oil combustion gases in the following order: peroxidase > biomass ≈ chlorophyll > protein > leaf injury. The endpoint responses of higher plants can be used to assess the suitability of particular plant species for use in urban afforestation areas with relatively intense vehicle traffic.

Impact of Different Combinations of Green Infrastructure Elements on Traffic-Related Pollutant Concentrations in Urban Areas

Urban air quality is a major problem for human health and green infrastructure (GI) is one of the potential mitigation measures used. However, the optimum GI design is still unclear. The purpose of this study is to provide some recommendation that could help in the design of the GI (mainly, the selection of locations and characteristics of trees and hedgerows). Aerodynamic and deposition effects of each vegetation element of different GI scenarios are investigated. Computational fluid dynamics (CFD) simulations of a wide set of GI scenarios in an idealized three-dimensional urban environment are performed. In conclusion, it was found that trees in the middle of the avenue (median strip) reduce street ventilation, and traffic-related pollutant concentrations increase, in particular for streets parallel to the wind. Trees in the sidewalks act as a barrier for pollutants emitted outside, specifically for a 45° wind direction. Regarding hedgerows, the most important effect on air quality is deposition and the effects of green walls and green roofs are limited to their proximity to the building surfaces.

Modelling Radiative and Convective Thermal Exchanges over a European City Center and Their Effects on Atmospheric Dispersion

Micro-meteorological studies of urban flow and pollution dispersion often assume a neutral atmosphere and often the three-dimensional variation in temperature fields and flow around buildings is neglected in most building energy balance models. The aim of this work is to present the results of development and validation of a three-dimensional tool coupling thermal energy balance of the buildings and modelling of the atmospheric flow and dispersion in urban areas. To do so, a 3D microscale atmospheric radiative scheme has been developed in the atmospheric module of the computational fluid dynamics (CFD) code Code_Saturne adapted to detailed building geometries. The full coupling of the radiative transfer and fluid dynamics models has been validated with idealized cases. In this paper, our focus is to simulate and compare with measurements the diurnal evolution of the brightness surface temperatures and the momentum and energy fluxes for a neighborhood in the city center of Toulouse, in the southwest part of France. This is performed by taking into account the 3D effects of the flow around the buildings and all thermal exchanges, in real meteorological conditions, and compare them to aircraft infrared images and in situ measurements on a meteorological mast. The calculation mesh developed for the city center and the simulation conditions for the selected day of the field campaign are presented. The results are evaluated with the measurements from the Canopy and Aerosol Particles Interactions in TOulouse Urban Layer experiment (CAPITOUL). In addition, the second purpose of this work is to investigate a hypothetical release of passive pollutant dispersion in the same area of Toulouse under different thermal transfer conditions for the street and the buildings surfaces: neutral and 3D radiative transfer heating. The presence of heat transfer continually modifies the airflow field while the airflow in the neutral case reaches a stationary state. Compared to the neutral case, taking into account the thermal transfer enhances the turbulence kinetic energy and vertical velocity (especially at the roof level) due to buoyancy forces. The simulation results also show that the thermal effects considerably alter the plume shape.

Long-term exposure to residential greenness and neurodegenerative disease mortality among older adults: a 13-year follow-up cohort study

BACKGROUND

Living in greener areas is associated with slower cognitive decline and reduced dementia risk among older adults, but the evidence with neurodegenerative disease mortality is scarce. We studied the association between residential surrounding greenness and neurodegenerative disease mortality in older adults.

METHODS

We used data from the 2001 Belgian census linked to mortality register data during 2001-2014. We included individuals aged 60 years or older and residing in the five largest Belgian urban areas at baseline (2001). Exposure to residential surrounding greenness was assessed using the 2006 Normalized Difference Vegetation Index (NDVI) within 500-m from residence. We considered all neurodegenerative diseases and four specific outcomes: Alzheimer's disease, vascular dementia, unspecified dementia, and Parkinson's disease. We fitted Cox proportional hazard models to obtain hazard ratios (HR) and 95% confidence intervals (CI) of the associations between one interquartile range (IQR) increment in surrounding greenness and neurodegenerative disease mortality outcomes, adjusted for census-based covariates. Furthermore, we evaluated the potential role of 2010 air pollution (PM_2.5 and NO₂) concentrations, and we explored effect modification by sociodemographic characteristics.

RESULTS

From 1,134,502 individuals included at baseline, 6.1% died from neurodegenerative diseases during follow-up. After full adjustment, one IQR (0.22) increment of surrounding greenness was associated with a 4-5% reduction in premature mortality from all neurodegenerative diseases, Alzheimer's disease, vascular and unspecified dementia [e.g., for Alzheimer's disease mortality: HR 0.95 (95%CI: 0.93, 0.98)]. No association was found with Parkinson's disease mortality. Main associations remained for all neurodegenerative disease mortality when accounting for air pollution, but not for the majority of specific mortality outcomes. Associations were strongest in the lower educated and residents from most deprived neighbourhoods.

CONCLUSIONS

Living near greener spaces may reduce the risk of neurodegenerative disease mortality among older adults, potentially independent from air pollution. Socioeconomically disadvantaged groups may experience the greatest beneficial effect.

Estimates of population exposure to atmospheric pollution and health-related externalities in a real city: The impact of spatial resolution on the accuracy of results

Health impacts of atmospheric pollution is an important issue in urban environments. Its magnitude depends on population exposure which have been frequently estimated by considering different approaches relating pollutant concentration and population exposed to it. However, the uncertainties due to the spatial resolution of the model used to estimate the pollutant concentration or due to the lack of representativeness of urban air quality monitoring station (AQMS) have not been evaluated in detail. In this context, NO₂ annual average concentration at pedestrian level in the whole city of Pamplona (Spain) modelled at high spatial resolution (~1 m) by Computational Fluid Dynamic (CFD) simulations is used to estimate the total population exposure and health-related externalities by using different approaches. Air pollutant concentration and population are aggregated at different spatial resolutions ranging from a horizontal grid cell size of 100 m × 100 m to a coarser resolution where the whole city is covered by only one cell (6 km × 5 km). In addition, concentrations at AQMS locations are also extracted to assess the representativeness of those AQMS. The case with a spatial resolution of 100 m × 100 m for both pollutant-concentration distribution and population data is used as a reference (Base case) and compared with those obtained with the other approaches. This study indicates that the spatial resolution of concentration and population distribution in the city should be 1 km × 1 km or finer to obtain appropriate estimates of total population exposure (underestimations <13%) and health-related externalities (underestimations <37%). For the cases with coarser resolutions, a strong underestimation of total population exposure (>31%) and health-related externalities (>76%) was found. On the other hand, the use of AQMS concentrations can induce important errors due to the limited spatial representativeness, in particular in terms of population exposure.

Evaluation of PM2.5 Retention Capacity and Structural Optimization of Urban Park Green Spaces in Beijing

Green space can effectively retain particles and improve air quality. However, most studies have focused on leaf-scale measurements or regional-scale model simulations, and few focus on individual trees. In this study, 176 urban park green spaces were selected within the 5th Ring Road in Beijing, and the i-Tree Eco model was used to estimate the PM2.5 retention levels of individual trees and sample plots. The results show that the retention capacity varied according to tree species. The PM2.5 retention of each sample plot was significantly affected by the tree coverage, species richness, mean tree height, mean crown width, and number of trees. The PM2.5 retention of urban park green spaces in the study area was estimated to be about 6380 t·year−1, and the air quality improvement rate was 1.62%. After structural optimizing, PM2.5 retention of the mixed coniferous and broad-leaved green space was as high as 80,000 g·year−1. This study studied the effects of trees on PM2.5 retention at multiple scales to fill the gaps in existing research at the scales of individual trees and communities, and it can serve as a reliable reference for the design and construction of green spaces aimed at improving air quality.

Study of the Effect of Vegetation on Reducing Atmospheric Pollution Particles

Atmospheric particulate matter (PM) is a major air pollutant. PM2.5 and PM10 pose particularly serious threats to the ecological environment and human health. Vegetation plays an important role in reducing the concentration of particles. Based on a long time series of air quality, meteorological, and vegetation coverage data in the Beijing–Tianjin–Hebei (BTH) region, the present paper evaluated the influence at the overall and built-up area scales and quantified the process involved in the dry settlement of particles on vegetation based on a mathematical model. The experimental results showed that (1) the total amounts of PM10 reduced by vegetation in the BTH area were 505,200 t, 465,500 t, 477,200 t and 396,500 t in 2015, 2016, 2017 and 2018, respectively, and the total amount of PM2.5 was reduced by 19,400 t, 19,200 t, 16,400 t and 12,700 t, respectively. The annual reduction in PM10 and PM2.5 from 2015 to 2018 by vegetation in the BTH region showed a downwards trend, and the annual reduction was mainly caused by the significant decrease in PM concentration. (2) More than 80% of the reduction in annual yield was concentrated in May–September, and a large leaf area was the main reason for the largest yield reduction in the growing season. The efficiency of PM reduction in forestland was approximately five–seven times that in grassland, and the deciduous broad-leaved forest was the main driver of this reduction in each forest. (3) The reduction in PM10 by vegetation was approximately 30 times that of PM2.5. However, the reduction in PM2.5 by vegetation should not be ignored because PM2.5 has a stronger correlation with human production and living activities. Increasing the area and density of green space via afforestation, returning farmland to forest and giving full play to the self-purification function of green spaces are very important to reducing and controlling the concentration of PM.

Not Only Trees Matter—Traffic-Related PM Accumulation by Vegetation of Urban Forests

In terms of the process of air purification, a lot of attention has been devoted to trees and shrubs. Little attention has been paid to herbaceous vegetation from the lower forest layers. Urban forests are often located on the outskirts of cities and surround exit roads where there is heavy traffic, generating particulate matter (PM) pollution. The aim of this study was to investigate the spread of PM from the road traffic in the air and to investigate how individual layers of urban forests accumulate PM. We conducted comparative analyses of PM accumulation on plants in five zones away from the road, into the forest, in the air, and in four vegetation layers: mosses, herbaceous plants, shrubs and trees. The results show that all forest layers accumulate PM. We show that PM is very efficiently accumulated by herbaceous plants growing along roadsides, and that the PM that was not deposited on herbaceous plants was accumulated by trees and shrubs. With increasing distance from the road into the forest, the PM content on herbaceous plants decreased and the accumulation on trees and shrubs increased. We estimated that PM concentration in the air dropped significantly in the front line of the trees, but it was still detectable up to 50 m into the forest. The results presented herein show that meadow vegetation and urban forests play a very important role in air purification. Our results provide a better understanding of the complexity of urban forest interactions and provide the basis for better planning of urban greenery.

High Spatial Resolution Assessment of the Effect of the Spanish National Air Pollution Control Programme on Street-Level NO2 Concentrations in Three Neighborhoods of Madrid (Spain) Using Mesoscale and CFD Modelling

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on Computational Fluid Dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality.

Evaluation of Vegetation Configuration Models for Managing Particulate Matter along the Urban Street Environment

As a green infrastructure component, urban street vegetation is increasingly being utilized to mitigate air pollution, control microclimates, and provide aesthetic and ecological benefits. This study investigated the effect of vegetation configurations on particulate matter (PM) flows for pedestrians in road traffic environments via a computation fluid dynamics analysis based on the road width (four and eight-lane) and vegetation configuration (single-, multi-layer planting, and vegetation barrier). Airflow changes due to vegetation influenced PM inflow into the sidewalk. Vegetation between roadways and sidewalks were effective at reducing PM concentrations. Compared to single-layer planting (trees only), planting structures capable of separating sidewalk and roadway airflows, such as a multi-layer planting vegetation barrier (trees and shrubs), were more effective at minimizing PM on the sidewalk; for wider roads, a multi-layer structure was the most effective. Furthermore, along a four-lane road, the appropriate vegetation volume and width for reducing PM based on the breathing height (1.5 m) were 0.6 m3 and 0.4 m, respectively. The appropriate vegetation volume and width around eight-lane roads, were 1.2–1.4 m3 and 0.8–0.93 m, respectively. The results of this study can provide appropriate standards for street vegetation design to reduce PM concentrations along sidewalks.

Understanding the effects of roadside hedges on the horizontal and vertical distributions of air pollutants in street canyons

Built-up environments limit air pollution dispersion in street canyons and lead to complex trade-offs between green infrastructure (GI) usage and its potential to reduce near-road exposure. This study evaluated the effects of an evergreen hedge on the distribution of particulate matter (PM₁, PM_2.5, PM₁₀), black carbon (BC) and particle number concentrations (PNCs) in a street canyon in West London. Instrumentation was deployed around the hedge at 13 fixed locations to assess the impact of the hedge on vertical and horizontal concentration distributions. Changes in concentrations behind the hedge were measured with reference to the corresponding sampling point in front of the hedge for all sets of measurements. Results showed a significant reduction in vertical concentrations between 1 and 1.7 m height, with maximum reductions of -16% (PM₁ and PM₁₀) and -17% (PM_2.5) at ∼1 m height. Horizontal concentrations revealed two zones between the building façade and the hedge, with opposite trends: (i) close to hedge (within 0.2 m), where a reduction of PM₁ and PM_2.5 was observed, possibly due to dilution, deposition and the barrier effect; and (ii) 0.2-3 m from the hedge, showing an increase of 13-37% (PM₁) and 7-21% (PM_2.5), possibly due to the blockage effect of the building, restricting dispersion. BC showed a significant reduction at breathing height (1.5 m) of between -7 and -50%, followed by -15% for PNCs in the 0.02-1 µm size range. The ELPI + analyser showed a peak of ∼30 nm. The presence of the hedge led to a ∼39 ± 32% decrease in total PNCs (0.006-10 µm), suggesting a greater removal in different modes, such as a 83 ± 12% reduction in nucleation mode (0.006-0.030 µm), 74 ± 15% in ultrafine (≤0.1 µm), and 34 ± 30% in accumulation mode (0.03-0.3 µm). These findings indicate graded filtering of particles by GI in a near-road street canyon environment. This insight will guide the improved design of GI barriers and the validation of microscale dispersion models.

Estimating NOx removal capacity of urban trees using stable isotope method: A case study of Beijing, China

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NO_x) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NO_x. The capacity of urban trees for NO_x removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m^-2 a^-1 across administrative regions, indicating that 1304 tons of NO_x could be potentially removed by urban trees in 2019. Our finding qualified the potential NO_x removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Urban road greenbelt configuration: The perspective of PM2.5 removal and air quality regulation

The establishment of the road green belt (RGB) is an effective means to reduce particle matter (PM_2.5) emissions from road traffic. This study tested the ability of 23 common tree species in Shenzhen to reduce PM_2.5 concentrations using field investigations and wind tunnel tests. The association between leaf microstructure and individual reduction ability was also analyzed. Finally, the impact of three RGB configurations (i.e., arbor, shrub, arbor + shrub) on road PM_2.5 dispersion and deposition was simulated using the ENVI-met three-dimensional aerodynamic model, based on which an optimal RGB configuration was proposed. There were three key findings of the tests. First, the wind speed was the main factor affecting the PM_2.5 concentration (54.2%), followed by vehicle flow (27.7%), temperature (14.2%), and time factor (7.6%). Second, the range of dry deposition velocity (V_d) was 0.04-6.4 m/s, and the dominant dust-retaining plant species were the evergreen trees, Ficus microcarpa and Ficus altissima, and the evergreen shrubs, Codiaeum variegatum and Fagraea ceilanica. A higher proportion of grooves or larger stomata would increase the probability that the blade would capture PM_2.5. Third, the shrub RGB demonstrated the best performance in terms of pollutant dispersion; its PM_2.5 concentration at the respiratory height (RH, 1.5 m) on the pedestrian crossing was 15-20% lower than the other RGB configurations. In terms of pollutant deposition, the arbor + shrub composite RGB was two-fold better than the other RGB configurations. Moreover, it was more advantageous to plant shrub RGBs in street canyons to achieve a balance between the lowest concentration and the largest deposition of PM_2.5 pollutants. The findings of this study will facilitate the RGB configurations with good dust retention ability.

How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne particles from a public health perspective - with implications for urban planning

Air pollution causes the largest death toll among environmental risks globally, but interventions to purify ambient air remain inadequate. Vegetation and green spaces have shown reductive effects on air-borne pollutants concentrations, especially of particulate matter (PM). Guidance on green space utilisation for air quality control remains scarce, however, as does its application in practise. To strengthen the foundation for research and interventions, we undertook a critical review of the state of science from a public health perspective. We used inter-disciplinary search strategies for published reviews on green spaces and air pollution in key scientific databases. Using the PRISMA checklist, we systematically identified reviews with quantitative analyses. For each of the presented PM mitigation mechanisms, we conducted additional searches focused on the most recent articles published between 2016 and early 2021. The included reviews differentiate three mitigation mechanisms of green spaces for PM: deposition, dispersion and modification. The most studied mechanism is deposition, particularly measures of mass and settling velocity of PM on plant leaves. We consolidate how green space setups differ by scale and context in their potentials to reduce peak exposures, stationary (point) or mobile (line) pollution sources, and the potentially most harmful PM components. The assessed findings suggest diverse optimisation options for green space interventions, particularly concerning plant selection, spatial setup, ventilation and maintenance - all alongside the consideration of supplementary vegetation effects like on temperature or water. Green spaces' reductive effects on air-borne PM concentrations are considerable, multi-mechanistic and varied by scale, context and vegetation characteristics. Such effect-modifying factors must be considered when rethinking public space design, as accelerated by the COVID-19 pandemic. Weak linkages amid involved disciplines motivate the development of a research framework to strengthen health-oriented guidance. We conclude on an urgent need for an integrated and risk-based approach to PM mitigation through green space interventions.

Impact of various vegetation configurations on traffic fine particle pollutants in a street canyon for different wind regimes

Vegetation establishment in urban areas is a potential solution to combat elevated particulate matter (PM) pollution, create cleaner environment for residents and enhance the sustainability of cities. However, vegetation effect at the points of interest in street-canyon on traffic pollutant from multiple interconnected factors (e.g., plant species, vegetation configurations, aerodynamic effect, deposition effect and complex wind regimes) is still not well studied. Therefore, taking roadside vegetation and street canyon as research objects, we evaluated vegetation effect (VE) for vegetation configurations (VCs) with several tree species on the dispersion, deposition, and distribution of traffic generated PM pollutant under different wind regimes. Results showed that (1) the transportation and distribution of traffic PM pollutant were different from wind regimes; (2) total VEs varied from -88.3% to 25.5%, depending on different VCs and wind regimes; perpendicular wind had the best VEs, while oblique wind had the worst VEs among the three wind directions; VEs of cypress were better than pine and poplar; VEs of one side planting were better than two sides planting. (3) the optimal VCs were found by each wind direction; two sides planting by shrub was suitable for parallel and oblique winds; for the perpendicular wind, the optimal VC was that two sides planting by cypress-shrub and increased canopy volume in the street center; and (4) VE were significantly correlated (P < 0.05) with vegetation parameters at lower wind speed, however, no correlations were found at higher wind speed under parallel wind; leeward wall VEs were significantly correlated with aerodynamic parameter (P < 0.001) while windward wall VEs and pedestrian-level VEs with deposition parameter (P < 0.05) under perpendicular wind; VEs were significantly decreased (P < 0.001) with aerodynamic parameter under oblique wind. The study highlights the impact of urban vegetation on air environment and provides insights for vegetation establishment from the viewpoint of improving air quality.

Effectiveness of plants and green infrastructure utilization in ambient particulate matter removal

Air pollution is regarded as an increasingly threatening, major environmental risk for human health. Seven million deaths are attributed to air pollution each year, 91% of which is due to particulate matter. Vegetation is a xenobiotic means of removing particulate matter. This review presents the mechanisms of PM capture by plants and factors that influence PM reduction in the atmosphere. Vegetation is ubiquitously approved as a PM removal solution in cities, taking various forms of green infrastructure. This review also refers to the effectiveness of plant exploitation in GI: trees, grasslands, green roofs, living walls, water reservoirs, and urban farming. Finally, methods of increasing the PM removal by plants, such as species selection, biodiversity increase, PAH-degrading phyllospheric endophytes, transgenic plants and microorganisms, are presented.

Contribution of Urban Forests to the Ecosystem Service of Air Quality in the City of Santo Domingo, Dominican Republic

A survey on pollutants that affect air quality was carried out at 27 points in the city of Santo Domingo, National District. The removal of air pollutants was estimated in relation to the city’s forest cover; using the iTree Canopy software. A principal components analysis and a correlation analysis was also performed to identify the association of these variables. The results show that the average percentage of green infrastructure in the sampling points was 26%. Also, positive correlation was identified between the presence of NO2 and SO2 at the sampling points. It was observed that the higher the presence of forest cover, the higher the concentration of CO and the lower the presence of pollutants. Although five hot spots were defined in terms of air pollution levels in the National District, the study does not show conclusive results regarding the relationship between green infrastructure and air quality in Santo Domingo. Results show that urban planning for environmental quality requires inter-institutional coordination, permanent ecological quality monitoring, and coordinated public policies to establish adequate indicators comparable to the World Health Organization standards.

Nature-Based Resilience: A Multi-Type Evaluation of Productive Green Infrastructure in Agricultural Settings in Ontario, Canada

Nature-based solutions such as green infrastructure present an opportunity to reduce air pollutant concentrations and greenhouse gas emissions. This paper presents new findings from a controlled field study in Ontario, Canada, evaluating the impact of productive applications of green infrastructure on air pollution and carbon dioxide concentrations across different agricultural morphologies compared to other non-productive applications. This study demonstrates that productive green infrastructure applications are as beneficial as non-productive applications in reducing ozone, nitrogen dioxide, and carbon dioxide concentrations. Nature-based solutions present an opportunity to build climate resilience into agricultural systems through supply-side mitigation and adaptation. The implementation of productive green infrastructure could be a viable agricultural practice to address multiple climate change impacts.

Where trees cannot grow - Particulate matter accumulation by urban meadows

It has already been proven that trees and shrubs, can efficiently remove particulate matter (PM) from air. However, almost nothing is known about PM accumulation by herbaceous plants (grasses and forbs) found in urban meadows. Meadows, unlike trees and shrubs, can be located close to roads, one of the main sources of PM in cites. The aim of this study was to investigate the tolerance to urban condition and PM accumulation in the immediate roads vicinity of selected plants species in urban meadows. PM accumulation of annual and perennial meadows was compared with that of lawns. Results were interpreted in the context of species composition, biomass production, soil conditions and ambient PM concentrations. Of the species grown in annual meadows, the highest PM accumulation was found in Achillea millefolium L., Chenopodium album L. and Echium vulgare L., while Centaurea scabiosa L., Echium vulgare L. and Convolvulus arvensis L. accumulated the largest amounts of PM in perennial meadows. PM deposition on plants was positively correlated with a feathery leaf shape. For species in the annual meadows, a positive correlation was also found between PM accumulation and the wax content on plants. The presence of hairs on leaves, leaf size and plant growth pattern had no effect on PM deposition on plants. PM accumulation in one square metre of urban meadow was on average greater than that of lawn, regardless of meadow species' composition, age and location. The greatest accumulation of PM was found in a perennial meadow with low biodiversity but the greatest biomass. It would appear that the biomass produced by meadows and canopy structure has a crucial impact on the amount of PM accumulated by meadow plants. The results obtained indicate that meadows could be an important element of nature-based solutions for mitigating air pollution in urbanised areas.

Green infrastructure can limit but not solve air pollution injustice

Outdoor air pollution contributes to millions of deaths worldwide yet air pollution has differential exposures across racial/ethnic groups and socioeconomic status. While green infrastructure has the potential to decrease air pollution and provide other benefits to human health, vegetation alone cannot resolve health disparities related to air pollution injustice. We discuss how unequal access to green infrastructure can limit air quality improvements for marginalized communities and provide strategies to move forward.

The application of land use regression model to investigate spatiotemporal variations of PM2.5 in Guangzhou, China: Implications for the public health benefits of PM2.5 reduction

Understanding the intra-city variation of PM_2.5 is important for air quality management and exposure assessment. In this study, to investigate the spatiotemporal variation of PM_2.5 in Guangzhou, we developed land use regression (LUR) models using data from 49 routine air quality monitoring stations. The R², adjust R² and 10-fold cross validation R² for the annual PM_2.5 LUR model were 0.78, 0.72 and 0.66, respectively, indicating the robustness of the model. In all the LUR models, traffic variables (e.g., length of main road and the distance to nearest ancillary) were the most common variables in the LUR models, suggesting vehicle emission was the most important contributor to PM_2.5 and controlling vehicle emissions would be an effective way to reduce PM_2.5. The predicted PM_2.5 exhibited significant variations with different land uses, with the highest value for impervious surfaces, followed by green land, cropland, forest and water areas. Guangzhou as the third largest city that PM_2.5 concentration has achieved CAAQS Grade II guideline in China, it represents a useful case study city to examine the health and economic benefits of further reduction of PM_2.5 to the lower concentration ranges. So, the health and economic benefits of reducing PM_2.5 in Guangzhou was further estimated using the BenMAP model, based on the annual PM_2.5 concentration predicted by the LUR model. The results showed that the avoided all cause mortalities were 992 cases (95% CI: 221-2140) and the corresponding economic benefits were 1478 million CNY (95% CI: 257-2524) (willingness to pay approach) if the annual PM_2.5 concentration can be reduced to the annual CAAQS Grade I guideline value of 15 μg/m³. Our results are expected to provide valuable information for further air pollution control strategies in China.

Effective reduction of roadside air pollution with botanical biofiltration

Currently no sustainable, economical and scalable systems have been developed for the direct removal of roadside air pollutants at their source. Here we present a simple and effective air filtering technology: botanical biofiltration, and the first field assessment of three different botanical biofilter designs for the filtration of traffic associated air pollutants - NO₂, O₃ and PM_2.5 - from roadside ambient air in Sydney, Australia. Over two six month research campaigns, we show that all of the tested systems filtered NO₂, O₃ and PM_2.5 with average single pass removal efficiencies of up to 71.5%, 28.1% and 22.1% respectively. Clean air delivery rates of up to 121 m³/h, 50 m³/h and 40 m³/h per m² of active green wall biofilter were achieved for the three pollutants respectively, with pollutant removal efficiency positively correlated with their ambient concentrations. We propose that large scale field trials of this technology are warranted to promote sustainable urban development and improved public health outcomes.

A review of strategies for mitigating roadside air pollution in urban street canyons

Urban street canyons formed by high-rise buildings restrict the dispersion of vehicle emissions, which pose severe health risks to the public by aggravating roadside air quality. However, this issue is often overlooked in city planning. This paper reviews the mechanisms controlling vehicle emission dispersion in urban street canyons and the strategies for managing roadside air pollution. Studies have shown that air pollution hotspots are not all attributed to heavy traffic and proper urban design can mitigate air pollution. The key factors include traffic conditions, canyon geometry, weather conditions and chemical reactions. Two categories of mitigation strategies are identified, namely traffic interventions and city planning. Popular traffic interventions for street canyons include low emission zones and congestion charges which can moderately improve roadside air quality. In comparison, city planning in terms of building geometry can significantly promote pollutant dispersion in street canyons. General design guidelines, such as lower canyon aspect ratio, alignment between streets and prevailing winds, non-uniform building heights and ground-level building porosity, may be encompassed in new development. Concurrently, in-street barriers are widely applicable to rectify the poor roadside air quality in existing street canyons. They are broadly classified into porous (e.g. trees and hedges) and solid (e.g. kerbside parked cars, noise fences and viaducts) barriers that utilize their aerodynamic advantages to ease roadside air pollution. Post-evaluations are needed to review these strategies by real-world field experiments and more detailed modelling in the practical perspective.

Analysis of Particulate Matter Concentration Intercepted by Trees of a Latin-American Megacity

Urban areas with trees provide several ecosystem services to citizens. There is a growing interest in ecosystem services for the removal of air pollutants such as particulate matter. The objective of this paper is to show a study on the variation of intercepted particulate matter concentration (IPMC) by tree leaves in the megacity of Bogotá (Colombia). The relationship between IPMC and PM2.5 concentrations observed in air quality stations in two urban zones with different air pollutions was studied. Influences of climate and leaf morphology variables on IPMC were also analyzed. The species under study were Ligustrum-lucidum, Eucalyptus-ficifolia, Tecoma-stans, Callistemon-citrinus, Lafoensia-acuminata, and Quercus-humboldtii. The results showed that leaf IPMC decreased as the PM2.5 concentration increased. Species that best described this trend were Ligustrum-lucidum and Lafoensia-acuminata. These two species also showed the largest IPMC in their leaves. Indeed, species that showed the largest leaf area were those with the highest IPMC. On average, it was observed that for each 5.0 µg/m3 increase in PM2.5 concentration the IPMCs of the species Ligustrum-lucidum and Lafoensia-acuminata decreased by 33.6% and 23.1%, respectively. When wind speed increased, there was also an increase in PM2.5 concentrations and a reduction in the leaf IPMCs.

Estimates of pedestrian exposure to atmospheric pollution using high-resolution modelling in a real traffic hot-spot

Atmospheric pollution is a very relevant risk for the human health, in particular in urban environments, where most people lives and high levels of pollution are found. Population exposure is traditionally estimated through concentration recorded at air quality monitoring stations (AQMS) or modelled at a spatial resolution of the order of 1 km². However, these methodologies have limitations in urban areas where strong gradients of concentration, even in the same street, exist. In addition, the movements of pedestrians make difficult to compute reliable estimates of pollutant concentration to which people are exposed to. In this context, the main objective of this study is to estimate the exposure of pedestrians to ambient nitrogen oxides (NOx) concentrations with high spatial resolution in a real urban traffic hot-spot under different methodologies. To achieve this objective, a novel methodology which combines high-resolution NOx concentrations from computational fluid dynamic (CFD) simulations with the pedestrian flows obtained by pedestrian mobility microsimulations is applied to an urban area of Madrid, Spain. High-resolution maps show pedestrian exposure peaks, at bus stops and crosswalks, that cannot be captured by the simpler methods based on spatial average concentration (SAC) or concentration measured in an AQMS. Total daily exposure obtained is 1.19 · 10⁹ person s μg m^-3, while SAC and AQMS concentration methods yielded 9-23% and 30-40% lower values. In conclusion, the proposed methodology allows to determine the areas with higher exposure in order to design local strategies to reduce the impact on human health. In addition, from a more general point of view, the total exposure in the studied area is better estimated by using spatial average concentration than through concentration recorded by AQMS. The assessment of the spatial representative of AQMS becomes necessary to use AQMS concentration to evaluate air quality and population exposure of an urban area.