Predicting the influence of trees on wind environment in pedestrian-level through numerical simulation

Predicting the influence of trees on wind environment in pedestrian-level through numerical simulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Predicting the influence of trees on wind environment in pedestrian-level through numerical simulation Lei Fan, Hongzuo Jia, Yan Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4905258/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Wind environment is closely related to people's lives and has a great influence on the comfort and safety of the environment. This research examines the influence of trees on wind environment in pedestrian-level. By integrating the theories of CFD simulation method and trees benefits, six canopy morphologies (Spheroid, Cone, Inverted Cone, Cylinder, Ellipsoid, Cuboid) models are proposed and validated. The PHOENICS is used for numerical simulation (144 scenarios), and the data are analyzed using Photoshop and linear regression model. It is found that the influence of trees on wind is linearly correlated with the varying crown width, trunk height and plant spacing. The influence of tree on wind velocity can be expressed by IF wind (the wind reducing ability) and AZ (the area of downwind deceleration zones). The framework and the numerical simulation in this paper are intended to support and guide future studies of wind comfort and wind safety of trees in pedestrian-level, and to contribute to improved wind environmental quality in urban areas through reasonable tree planting. Earth and environmental sciences/Environmental sciences/Environmental impact Earth and environmental sciences/Ecology/Forestry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Wind is an important component of atmospheric environment. Wind environment is closely related to people's lives and has a great influence on the comfort and safety of the environment. Suitable wind speed and ventilation are conducive to the diffusion of atmospheric pollutants, reduce urban heat island effect, improve urban air quality, and improve the thermal comfort of outdoor activities 1–5 . However, with the continuous urbanization, the appearance of a large number of artificial structures has affected the urban wind speed, wind direction and ventilation efficiency, which further worsens the urban heat island effect and air pollution 6 . In recent decades, the pedestrian’s outdoor thermal comfort has been critical for designing sustainable cities, which can be affected by wind flow in urban spaces 4, 7 . Wind speed, an important factor impacting thermal comfort, has been shown to have various impacts on pedestrians depending on the specific surrounding conditions 8–11 . Pedestrian-level wind environment in urban areas has a significant impact on the quality of urban dwellers' outdoor thermal comfort 3, 12 . The analysis and optimization of pedestrian-level wind environment is of great significance for improving urban living environment and constructing sustainable urban space. And therefore, the pedestrian-level wind environment has attracted the attention of academics. Given the growing call for more vegetation in cities, it is important to study the wind resistant of urban trees in order to address outdoor natural ventilation problem in the landscape planning 13 . Previous studies have shown trees are more effective climate moderators than the other green elements 14–16 . Trees have always played a crucial role for human beings, providing several ecosystem services in urban areas. It can regulate the local microclimate environment of the city, alleviate the heat island effect, hinder and adsorb the particulate pollutants, absorb the gaseous pollutants and so on 17–21 . And the trees can alter the thermal-stress conditions by reducing wind-speed, changing wind-directions, and improving the comfort and health of the wind environment 22–28 . The main methods used to study the flow field around trees include in situ measurements, wind tunnel tests and numerical simulations. In recent years, the airflow field around trees has been widely simulated using Computational Fluid Dynamics (CFD) technology 9, 22, 29–30 . However, in most urban construction activities, designers only estimate whether the urban space in the scheme can meet the requirements of ventilation in summer and windproof in winter based on experience, and habitually use plants in aesthetic design and vertical design, but ignore their important role in improving wind environment, and there is a lack of assessment studies on the influence factors of trees on wind environment. Therefore, it is necessary to have a comprehensive understanding of the changing laws of the flow field around trees to guide urban tree planting, which is of great practical significance for building a comfortable and healthy urban wind environment, creating a liveable urban ecological environment and achieving sustainable urban development. There are many studies on wind environment based on tree characteristics. Zheng's study show that tree crowns, created by branches, leaves and twigs, can provide shade and reduce wind speed 31 . Lai et al. 32 found that the wind load a tree withstood is mainly applied to its crown, whose morphology and structure directly affect the degree of wind load given a certain wind condition. Cao et al. 33 and Zhang et al. 34 analyzed the relationships between changes in tree characteristics and wind speed, such as crown displacement, windward area and porosity. Mayaud et al. investigated the effects of a single tree, a grass clump, and a shrub on turbulent wind flow and discovered that wind velocity can be reduced by up to 70% in the lee of vegetation 35 . Amani-Beni et al. have investigated the effects of wind loading on three dimensional tree models using numerical simulation with implications for urban design 36 . In some papers, the wind environment is studied by taking individual trees as examples. Five-year-old white fir trees ( Abides concolor ) were tested as the wind break model in Lee and Lee’s work 23 . The drag coefficients of four common subtropical trees ( Ficus microcarpa , Mangifera indica , Michelia alba and Bauhinia blakeana ) have been obtained by using wind tunnel measurements 37 . The overall airflow variation in the downwind zone of a single tree is usually represented by the airflow variation in the central axis of the tree, based on which studies have developed airflow field models around single plants 35, 38 . Some scholars are also very concerned wind speed on the leeward side of trees: Zeng et al. point out the trees can cause a decrease in wind speed on their leeward side and limit heat dissipation 28 . Cheng et al. found out the downwind deceleration zone based on the trend of wind speed in their experiments 38 . For wind environmental improvements, the tree species selection and arrangement is the important parameters to be considered by planners and designers. So it is worth to be investigated for a better understanding of the wind environment which determine pedestrian comfort. The analysis of wind behavior behind trees has become an important task to address at the planning stage of tree planting. Raman et al. pointed out that isolated trees are found providing better cooling than the loosely clustered ones, containing open spaces in between 39 . Single tree is the basic unit of urban green layouts. Different types of green layout can be formed by planting multiple single trees together. In order to research the effect of green layouts on wind environment, it is necessary to study the wind environment of single tree. However, the wind environment of single tree is still not fully understood, especially from the point of view of tree canopy morphologies. The complexity of the architecture of plant canopies makes the flow phenomena within and around the canopies extremely complex and difficult to predict 40 . Many factors can affect wind mitigation including wind direction, tree type, stem height, tree height, trunk height, crown width, distance between trees 41–42 . In order to figure out how crown width, trunk heights, and plant spacing of single tree influence the wind velocity, the PHOENICS CFD numerical simulation was performed in this study. Through the study of varying canopy morphologies of trees, to obtain downwind speeds data of the pedestrian-level. The goal of the present work is threefold: ( 1 ) to explore the influence of crown width, trunk height and plant spacing on wind velocity; ( 2 ) to calculate the area of downwind deceleration zones of varying crown width, trunk height above ground, and plant spacing; ( 3 ) to find out the relationship between the influence of trees on wind (wind velocity and downwind deceleration zones) and varying tree’s parameters. Materials and Methods Study area. Shenyang is located in the south of northeast China and the middle of Liaoning Province. It is the capital city of Liaoning Province and the central hub city of Central Liaoning City Group, the seventh largest city group in China. It is located at 41.80° North Latitude and 123.43° East Longitude and has a total area of 12,948 km 2 . Shenyang is located in the monsoon area with high frequency and strong wind, which brings many negative effects to the daily life of city residents. The rapid urbanization has an influence on the climatic environment of Shenyang, especially the wind and thermal environment in the central urban area. As a result, the urban heat island effect is enhanced in Shenyang in summer, and haze weather often occurs in winter heating period, which greatly affects the daily life and health of urban residents 43,44 . In this paper, trees planted in Shenyang Agricultural University were selected as reference for numerical simulation of plant parameters. According to the survey data, there are 62 species of trees in Shenyang Agricultural University. The main tree species are Abies nephrolepis , Picea koraiensis , Larix kaempferi , Pinus koraiensis , Pinus tabuliformis , Juniperus chinensis , Taxus cuspidata , Robinia pseudoacacia , Gleditsia japonica , Acer truncatum , Quercus mongolica , Ginkgo biloba , Sophora japonica , Prunus davidiana , Prunus padus , Salix matsudana , Salix babylonica , Juglans mandshurica , Populus alba , Sophora japonica , Catalpa ovata , Ulmus pumila , Fraxinus mandshurica , and Syringa reticulata . These tree species have strong adaptability and good growth characteristics, and are widely used in urban greening. Numerical Simulation by PHOENICS. In this paper, PHOENICS is selected to simulate the effect of trees on wind environment. Ecological Housing Technology Assessment Manual of China (2003) stipulates that at the pedestrian height, that is, 1.5 m above the surface, the wind speed can only be considered comfortable when it is less than 5 m/s, and it cannot be considered comfortable when it exceeds this value 45 . Assessment Standard for Green Building of China stipulates that the wind speed in the pedestrian area around the building should be less than 5m/s 46 . In addition, the studies also found that people's sitting, standing and walking behaviors are relatively comfortable when the ambient wind speed is between 0−5.0m/s, while people feel uncomfortable when the ambient wind speed exceeds 5m/s 7 . Therefore, the inlet wind speed of simulation is set at 5m/s. At present, two equation models, k-ε model and RNG k-ε model, are the most widely used in the numerical simulation of outdoor wind environment. The simulation results of these two models are close to the actual wind field 47 . Among them, the overall accuracy of RNG k-ε model is higher, and is chosen for the study of this paper. In this study, the calculation area is set as 210m×210m×50m, the tree is located in the center of the calculation area, the inlet wind direction is set as N, and the inlet wind speed is 5m/s. Previous studies have simplified tree canopies into ellipsoid, cone, cylinder, cuboid, square, rectangular and other geometries to analyze the effect of trees on the flow field 48,49 . Liu et al. stated that a better understanding of the airflow around a single plant is fundamental and important in the study of the flow field across multiple plants 48 . Based on the tree species in site investigation, tree canopy morphologies were simplified into six types in this paper: Spheroid, Cone, Inverted Cone, Cylinder, Ellipsoid, and Cuboid (Fig. 1). In the early period, the tree parameters of Shenyang Agricultural University were measured and found that the tree average height of 8 m accounted for a large proportion of trees, and the average DBH was 0.25m. Therefore, in the simulation experiment, the height of a single tree was set to 8 m, and the DBH was set to 0.25m. The 3D plant modeling is carried out by using Rhino software. Then the model is imported into PHOENICS and the canopy model parameters are set as "porous media parameter module FOLIAGE", regardless of the internal structure of the canopies. This paper explores three scenarios of the influence of trees on wind environment (Table 1 ). S1 (48 sub-scenarios): The tree height, trunk height, and DBH are set to fixed value, so as to explore the influence of varying crown widths on wind velocity; S2 (54 sub-scenarios): The DBH and crown width are set to fixed value, so as to explore the influence of varying trunk heights on wind velocity; S3 (42 sub-scenarios): The tree height, trunk height, DBH, and crown width are set to fixed value, so as to explore the influence of varying plant spacing of two trees on wind velocity. Through numerical simulation, wind velocity distribution map of varying scenarios can be obtained (Fig. 2). The map can show the effect of trees on wind velocity weakening and direction changing. In order to describe the pedestrian-level influence trend of trees on wind, wind velocity distribution map is divided into 10 levels of downwind deceleration zones Z0, Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, Z9 (Table 2 ). A range from Z0 to Z9 indicates that the trees is weakening the wind velocity more and more, so the weights Z0 to Z9 are calculated using Analytic Hierarchy Process. The downwind deceleration zones have a elliptical shape from the top view. This study used Photoshop histograms to calculate the pixels of each Zn and then converted to the area. According to the area and weight of Zn, the influence value of trees on wind velocity (IF wind ) in each scenario was calculated. Where Zn is the area of downwind deceleration zone, W Zn is the weight of the downwind deceleration zone. Results Influence of crown widths on wind velocity. According to the wind velocity distribution maps, with the increase of crown width, there was a strong positive correlation between crown width and IF wind (Fig. 3a). Among them, Ellipsoid (R 2 = 0.98848) is the strongest correlation between crown width and IF wind , while Cylinder (R 2 = 0.90431) is the weakest. On the whole, the min IF wind appeared at 1m (0.5 m) crown width and the max IF wind appeared at 8m (4.0 m) crown width. When the crown width is 1m (0.5 m), IF wind ranges from 0.02 (Cone) to 0.60 (Cuboid); crown width is 2m (1.0 m), IF wind ranges from 4.43 (Inverted Cone) to 9.87 (Spheroid); crown width is 3 m (1.5 m), IF wind ranges from 2.19 (Cuboid) to 12.09 (Cylinder); crown width is 4 m (2.0 m), IF wind ranges from 11.19 (Cone) to 16.86 (Cylinder); crown width is 5m (2.5 m), IF wind ranges from 17.08 (Cone) to 35.70 (Cylinder); crown width is 6m (3.0 m), IF wind ranges from 24.59 (Ellipsoid) to 36.03 (Spheroid); crown width is 7 m (3.5 m), IF wind ranges from 30.66 (Ellipsoid) to 58.32 (Spheroid); crown width is 8 m (4.0 m), IF wind ranges from 35.08 (Ellipsoid) to 76.24 (Spheroid). According to the wind velocity distribution maps. Wherever each sub-scenario contains several downwind deceleration zones, these zones are continuous. There was a strong positive correlation between crown width and the area of downwind deceleration zones (AZ) (Fig. 3b). Linear relationship analysis model shows that the strongest positive correlation between crown width and AZ is Ellipsoid (R 2 = 0.99054), and the weakest is Cylinder (R 2 = 0.78106). On the whole, the min AZ appeared at 1 m (0.5 m) crown width and the max AZ appeared at 8 m (4.0 m) crown width. When the crown width is 1 m (0.5 m), AZ ranges from 0.96 m 2 (Cone) to 39.87 m 2 (Cuboid); crown width is 2 m (1.0 m), AZ ranges from 215.02 m 2 (Cuboid) to 462.95 m 2 (Spheroid); crown width is 3 m (1.5 m), AZ ranges from 73.02 m 2 (Cuboid) to 372.17 m 2 (Ellipsoid); crown width is 4 m (2.0 m), AZ ranges from 248.54 m 2 (Cuboid) to 617.64 m 2 (Inverted Cone); crown width is 5 m (2.5 m), AZ ranges from 352.49 m 2 (Cone) to 631.16 m 2 (Cylinder); crown width is 6 m (3.0 m), AZ ranges from 475.16 m 2 (Cylinder) to 1128.13 m 2 (Inverted Cone); crown width is 7 m (3.5 m), AZ ranges from 607.49 m 2 (Ellipsoid) to 1766.09 m 2 (Inverted Cone); crown width is 8 m (4.0 m), AZ ranges from 784.52 m 2 (Cylinder) to 2084.62 m 2 (Inverted Cone). Influence of trunk heights on wind velocity. Wind velocity distribution maps show that with the increase of trunk height, the corresponding IF wind value also changes. Trunk heights of Spheroid, Cone, Cylinder, Ellipsoid, and Cuboid are negatively correlated with IF wind values (Fig. 4a). Among them, Spheroid (R 2 = 0.94455) is the strongest correlation between trunk height and IF wind , while Cone (R 2 = 0.01252) is the weakest. Trunk height of Inverted Cone (R 2 = 0.83173) is positively correlated with IF wind values. For every tree canopy morphology, the distribution of min and max IF wind is irregular. When the trunk height is 0.0 m, IF wind ranges from 7.01 (Cuboid) to 42.21 (Cylinder); trunk height is 0.5 m, IF wind ranges from 6.06 (Cuboid) to 47.24 (Cylinder); trunk height is 1.0 m, IF wind ranges from 4.64 (Cuboid) to 51.72 (Cylinder); trunk height is 1.5 m, IF wind ranges from 2.69 (Cuboid) to 37.01 (Cylinder); trunk height is 2.0 m, IF wind ranges from 2.24 (Cuboid) to 33.92 (Cylinder); trunk height is 2.5 m, IF wind ranges from 1.44 (Cuboid) to 30.41 (Cylinder); trunk height is 3.0 m, IF wind ranges from 0.37 (Cuboid) to 25.43 (Cylinder); trunk height is 3.5 m, IF wind ranges from 0 (Cuboid) to 26.23 (Cone); trunk height is 4.0 m, IF wind ranges from 0 (Cuboid) to 25.55 (Cone). According to the wind velocity distribution maps, the AZ changes with the increase of trunk height. Trunk heights of Inverted cone (R 2 = 0.96664), Cone (R 2 = 0.71474), and Cylinder (R 2 = 0.07178) are positively correlated with AZ (Fig. 4b). Trunk heights of Cuboid (R 2 = 0.90109), Spheroid (R 2 = 0.48754), and Ellipsoid (R 2 = 0.43103) are negatively correlated with AZ. For every tree canopy morphology, the distribution of min and max AZ is irregular. When the trunk height is 0.0 m, AZ ranges from 163.63 m 2 (Ellipsoid) to 377.36 m 2 (Cylinder); trunk height is 0.5 m, AZ ranges from 164.13 m 2 (Ellipsoid) to 450.25 m 2 (Cone); trunk height is 1.0 m, AZ ranges from 162.37 m 2 (Ellipsoid) to 499.05 m 2 (Cone); trunk height is 1.5 m, AZ ranges from 157.36 m 2 (Cuboid) to 507.28 m 2 (Cone); trunk height is 2.0 m, AZ ranges from 142.14 m 2 (Cuboid) ~ 601.64 m 2 (Cone); trunk height is 2.5 m, AZ ranges from 95.06 m 2 (Cuboid) to 556.33 m 2 (Cone); trunk height is 3.0 m, AZ ranges from 24.47 m 2 (Cuboid) to 544.26 m 2 (Cone); trunk height is 3.5 m, AZ ranges from 0 m 2 (Cuboid) to 615.00 m 2 (Cone); trunk height is 4.0 m, AZ ranges from 0 m 2 (Cuboid) to 587.33 m 2 (Cone). Influence of plant spacing on wind velocity. Wind velocity distribution maps show that with the increase of plant spacing, the corresponding IF wind value also changes. Plant spacing of Inverted cone (R 2 = 0.20524), Spheroid (R 2 = 0.18993), and Cone (R 2 = 0.03381) are positively correlated with IF wind values (Fig. 5a). Plant spacing of Ellipsoid (R 2 = 0.60740), Cylinder (R 2 = 0.11324), and Cuboid (R 2 = 0.03384) are negatively correlated with IF wind values. For every tree canopy morphology, the distribution of min and max IF wind is irregular. When the plant spacing is 3 m, IF wind ranges from 7.06 (Ellipsoid) to 18.16 (Cylinder); plant spacing is 6 m, IF wind ranges from 8.77 (Ellipsoid) to 24.22 (Cylinder); plant spacing is 9 m, IF wind ranges from 7.51 (Ellipsoid) to 20.81 (Cylinder); plant spacing is 12 m, IF wind ranges from 7.36 (Ellipsoid) to 19.89 (Cylinder); plant spacing is 15 m, IF wind ranges from 6.52 (Ellipsoid) to 19.42 (Cylinder); plant spacing is 18 m, IF wind ranges from 5.38 (Ellipsoid) to 19.32 (Cylinder); plant spacing is 21 m, IF wind ranges from 5.84 (Ellipsoid) to 19.01 (Cylinder). Wind velocity distribution maps show that a two-tailed feature appears in downwind deceleration zones. The AZ increased first and then decreased with the increase of planting spacing. Plant spacing of Cylinder (R 2 = 0.83393), Spheroid (R 2 = 0.56241), Inverted cone (R 2 = 0.33146), Cone (R 2 = 0.24663), and Cuboid (R 2 = 0.11994) are positively correlated with AZ (Fig. 5b). Plant spacing of Ellipsoid (R 2 = 0.33901) are negatively correlated with AZ. For every tree canopy morphology, the distribution of min and max AZ is irregular. When the plant spacing is 3 m, AZ ranges from 201.35 m 2 (Ellipsoid) to 367.82 m 2 (Cylinder); plant spacing is 6 m, AZ ranges from 269.25 m 2 (Cuboid) to 461.37 m 2 (Cylinder); plant spacing is 9 m, AZ ranges from 243.10 m 2 (Ellipsoid) to 478.14 m 2 (Cylinder); plant spacing is 12 m, AZ ranges from 241.17 m 2 (Ellipsoid) to 506.31 m 2 (Cylinder); plant spacing is 15 m, AZ ranges from 212.48 m 2 (Ellipsoid) to 529.94 m 2 (Cylinder); plant spacing is 18 m, AZ ranges from 182.06 m 2 (Ellipsoid) to 547.07 m 2 (Cylinder); plant spacing is 21 m, AZ ranges from 188.62 m 2 (Ellipsoid) to 540.79 m 2 (Cylinder). Discussion In order to concretize and digitally present the wind environment at the pedestrian-level, this paper conducted a numerical simulation study on six canopy morphologies of trees in multi-scenarios. It is found that the changes of wind velocity and downwind deceleration zones influence by trees. The IF wind and AZ values of trees with varying crown width, trunk height and plant spacing have obvious differences. The influence of plants on the pedestrian level wind environment is the focus of scholars 8,9,10,11,50,51,52 . Visualization and parameterization of tree canopy morphologies is the basic setting of these researches 53,54 . In this paper, the simulation experiments of six canopy morphologies have enriched the types of similar numerical simulation of tree canopy shape. The wind environment simulation research on the whole green space shows the overall situation of wind environment 15, 20 , but the wind environment of "single tree", the basic element of green space, is still an important topic. The numerical characteristics of single tree wind environment need to be solved fundamentally for the diversified planting forms of greening. It is necessary to numeralize the wind environment of the tree, so as to further quantify the influence of the tree on wind velocity. Based on previous studies, this paper designed three scenarios (S1, S2, and S3), including 144 sub-scenarios, to simulate the pedestrian-level wind environment of individual trees and coupled planting. Wind velocity distribution map shows 10 sub-zones (Fig. 2), all of which are downwind deceleration zones 27 . According to the area of the sub-zones and the corresponding weight, the IF wind of the scenario can be calculated. This is different from the expression in previous studies, which used the multiple of tree height to represent the length of wind speed zone, while this paper used the area to represent 27 . "IF wind " is a new term proposed in this paper, which is intended to explain the influence of trees on wind velocity reduction in a quantitative way. In the experiment, the IF wind of six canopy morphologies changed with the varying of crown width, trunk height and plant spacing. The focus of this paper is to use PHOENICS to simulate the effects of crown width (S1), trunk height (S2) and plant spacing (S3) on wind velocity. To interpret, the findings suggest that for the same tree canopy morphology, the crown width had a strong positive correlation with both IF wind and AZ. With the increase of tree crown width, the corresponding IF wind and AZ increased (Fig. 6a). Compared with previous studies, it is found that the influence of different canopy size on wind velocity is of more practical significance, thus supporting the selection of suitable crown width according to different wind speed reduction needs, which is more targeted. In addition, the trunk height is negatively correlated with the IF wind value, which is the same as the research result of Zhao et al. "There is a significant negative correlation between the trunk height from the ground and the wind environment" 55 , but the Inverted Cone canopy morphology in this paper is positively correlated with the IF wind value (Fig. 4a), which can be used as a supplement to this theory. The correlation between trunk height and AZ value was observed in two cases: the positive correlations are Cone, Inverted Cone, and Ellipsoid; the negative correlations are Spheroid, Cylinder, and Cuboid. However, whether the correlation is positive or negative, the maximum value of AZ appears in the median range of the trunk height (Fig. 6b): Spheroid (1.5m), Cone (3.5m), Inverted Cone (3.5m), Cylinder (2.0m), Ellipsoid (2.5m), and Cuboid (0.5m); The minimum value of AZ appears when the plant spacing is the largest or the smallest: Spheroid (4.0m), Cone (0.0m), Inverted Cone (0.0m), Cylinder (0.0m), Ellipsoid (3.5m), and Cuboid (4m). The Numerical simulation results of crown width and trunk height same to the results of Hosseinzadeh and Keshmiri’s 51 viewpoint "Younger trees with crowns closer to the ground mitigate wind more. However, older trees with wider crowns are able to decrease wind more.” It also coincides with to the discussion of Huang et al. 19 "the trunk height affects significantly the flow". Finally, the correlation between plant spacing and IF wind value is also in two cases: Spheroid, Cone, and Inverted Cone are positively correlated with IF wind ; Cylinder, Ellipsoid, and Cuboid are negatively correlated with IF wind . The reason is caused by the influence of the wind environment generated by the canopy morphologies. However, they have a common feature, that is, the maximum value of IF wind appears in the median range of plant spacing: Spheroid (9m), Cone (6m), Inverted Cone (15m), Cylinder (6m), a - IF wind with crown width s - IF wind with trunk height c- IF wind with plant spacing Figure 6. The linear regression model of the IF wind with AZ Ellipsoid (6m), and Cuboid (12m) (Fig. 6c). Most of the minimum values of IF wind occur when the plant spacing is closest or farthest: Spheroid (3m), Cone (3m), Inverted Cone (3m), Cylinder (3m), Ellipsoid (18m), and Cuboid (21m). Plant spacing is positively correlated with AZ values, except for Ellipsoid. Although this paper presupposes 10 downwind deceleration zones, only Cuboid's trunk height at 0.0 m, 0.5 m, and 1.0 m includes all zones. The simulation results of other scenarios include only 1–9 zones. The findings seems indicate that no matter how many zones are included in the sub-scenario, these zones are continuous, and there is no disconnection of zones’ serial number. Moreover, in most cases, the area of these zones is progressively reduced as the serial number increases. When Cuboid had trunk heights of 0.0 m, 0.5 m, and 1.0 m, their ability to reduce wind velocity reached 87.6%, exceeding that of Mayaud et al. 35 stated "that wind velocity can be reduced by up to 70% in the lee of vegetation", which may explained by the differences in inlet wind speed and canopy details. This paper focuses on the influences of crown width (S1), trunk height (S2) and plant spacing (S3) on wind velocity of single trees in pedestrian-level. The relationship between the varying parameters and the IF wind /AZ values was discussed. So is there a correlation between the AZ and IF wind ? To further validate this question, a linear analysis was performed. The test results reveal that except for the trunk height and plant spacing scenarios of a - crown width b - trunk height c- plant spacing Figure 7. The linear regression model of the IF wind with AZ Cylinder, the AZ is positively correlated with IF wind in other scenarios (Fig. 7). Which provides additional evidence on the IF wind / AZ by trees. Based on the above analysis, we can draw the following results: For most scenarios, the larger the canopy width, the larger its IF wind and AZ values; In case of the trunk height and planting spacing scenarios, both the IF wind and AZ have the maximum values, and after the maximum value appears, there is a trend of gradual decrease. The results show that the varying of crown width (S1), trunk height (S2) and plant spacing (S3) all have an influence on wind velocity, and the maximum and minimum values of IF wind and AZ as well as their changing trends are simulated. The influence of crown width on wind velocity is less influenced and limited by canopy morphology. However, the influence of trunk height and plant spacing on wind velocity is limited by crown morphology. Our research results enrich the canopy morphologies setting for numerical simulation of tree’s wind environment, and the influence of crown width, trunk height and plant spacing on wind environment also strongly prove our initial hypothesis. The conclusion of this study provides a reference for the diversified planting design of today. Conclusion This research examines the influence of trees on wind environment t in pedestrian-level. By integrating the theories of CFD simulation method and trees benefits, six canopy morphology spatial models are proposed and validated. The PHOENICS is used for numerical simulation (144 scenarios), and the data are analyzed using Photoshop and linear regression model. It is found that crown width, trunk height, and plant spacing influence on wind velocity. Furthermore, our findings suggest that IF wind and AZ can represent the influence value of trees on wind velocity. Because the crown width, trunk height and plant spacing all have an influence on the two indicators. With the findings, our study makes several theoretical and practical contributions. Firstly, the influence of trees on wind is linearly correlated with the varying crown width, trunk height and plant spacing. The influence of tree on wind velocity can be expressed by IF wind and AZ, where IF wind value indicates the wind reducing ability of tree; AZ value shows the area of downwind deceleration zones. This result enriches the wind environment theory of trees. More importantly, the crown morphology affects the tree’s influence on wind velocity. Because there were varying degrees of positive and negative linear correlations between IF wind and trunk height / plant spacing, and between AZ and trunk height / plant spacing. This finding to modify the detail theory of the negative linear correlation between trunk height / plant spacing and wind velocity. Except for the scenarios of Cylinder’s trunk height and plant spacing, the AZ values in other scenarios where the crown width, trunk height and plant spacing are all positively correlated with the IF wind values. Additionally, the findings indicates that no matter how many downwind deceleration zones are included in the scenarios, these zones are continuous, and there is no disconnection of zones’ serial number. Moreover, in most cases, the area of these zones is progressively reduced as the serial number increases. We propose a new targeted wind velocity measurement system of trees developed using PHOENICS. The framework and the numerical simulation in this paper are intended to support and guide future studies of wind comfort and wind safety of trees in pedestrian-level, and to contribute to improved wind environmental quality in urban areas through reasonable tree planting. Our research results also provide relevant data reference for landscape architects and urban planners, and can provide numerical reference for the reasonably use of tree species with their IF wind and AZ. Which is of great practical significance for building a comfortable and healthy urban wind environment, creating a liveable urban ecological environment and achieving sustainable urban development. The numerical simulation experiment is an exploratory attempt. The simulation of wind velocity of tree is carried out in a ideal laboratory environment. There are some differences between the experimental results and the real environment. Therefore, in the follow-up study, it is necessary to modify and improve the simulation data combined with the field measured data. Declarations Competing interests The authors declare no competing interests. Funding The research was supported by Research Fund project of Liaoning Provincial Department of Education (JYTMS20231295), Social Science Research Fund project of Liaoning Province (L23BDJ002), University level Research Fund project of Shenyang Agricultural University (X2022005). Author Contribution L.F. and Y.Z. wrote the main manuscript text, and H. Z. J. prepared figures. All authors reviewed the manuscript. Data Availability All data generated or analysed during this study are included in this article (and its supplementary information files). References Yang, L. & Li, Y. Thermal conditions and ventilation in an ideal city model of Hong Kong. Energ. Buildings. 43 (5), 1139–1148 (2011). Priyadarsini, R., Hien, W. N. & David, C. K. W. Microclimatic modeling of the urban thermal environment of Singapore to mitigate urban heat island. Sol. Energy. 82 (8), 727–745 (2008). Shui, T. T. et al. Assessment of pedestrian-level wind conditions in severe cold regions of China. Build. 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Quantification of thermal stress abatement by trees, its dependence on morphology and wind: A case study at Patna, Bihar, India. Urban For. Urban Gree. 63, 127213 (2021). Endalew, A. M. et al. Modelling airflow within model plant canopies using an integrated approach. Comput. Elevtron. Agr. 66, 9–24 (2009). Gromke, C. & Ruck, B. Influence of trees on the dispersion of pollutants in an urban street canyon-Experimental investigation of the flow and concentration field. Atmos. Environ. 41, 3287–3302 (2007). Gromke, C. et al. CFD analysis of transpirational cooling by vegetation: Case study for specific meteorological conditions during a heat wave in Arnhem, Netherlands. Build. Environ. 83, 11–26 (2015). Li, L. G. et al. Urban heat island intensity and its grading in Liaoning Province of Northeast China. Chinese Journal of Applied Ecology. 23 (5), 1345–1350 (2012). Ma, Y. J. et al. Research Advances on Atmospheric Environment Research in Multi-cities in the Middle of Liaoning Province. Chinese Journal of Advances in Meteorological Science and Technology. 2 (2), 19–24 (2012). Nie, H. S. Ecological Housing Technology Assessment Manual of China . (China Architecture Publishing & Media Co., Ltd., 2013). Ministry of Housing and Urban-Rural Development of China. Assessment Standard for Green Building of China . (GB/T 50378, 2019). Feng, B. et al. Buildings Wind Environment Stratified Optimization Strategy. Chinese Journal of Science Technology and Engineering. 19, 18–26 (2019). Liu, C., Zheng, Z., Cheng, H. & Zou, X. Airflow around single and multiple plants. Agr. Forest Meteorol. 252, 27–38 (2018). Li, R. et al. Numerical investigation of the blockage effect of trees on airflow distributions in a wind tunnel. Build. Environ. 263, 111848 (2024). Blocken, B., Janssen, W. D. & Hooff, T. CFD simulation for pedestrian wind comfort and wind safety in urban areas: General decision framework and case study for the Eindhoven University campus. Environ. Modell. Softw. 30, 15–34 (2012). Hosseinzadeh, A. & Keshmiri, A. Computational Simulation of Wind Microclimate in Complex Urban Models and Mitigation Using Trees. Buildings. 11, 112 (2021). Fang, F. M., Chang, J. C., Li, Y. C., Chung, C. Y. & Chan, M. H. Shelter Effect of PedestrianWind behind Row Trees in a Line Arrangement. Forests. 13, 392 (2022). Wang, L., Su, J., Gu, Z. & Tang, L. Numerical study on flow field and pollutant dispersion in an ideal street canyon within a real tree model at different wind velocities. Comput. Math. Appl. 81, 679–692 (2021). Chan, W. L. et al. Wind Loading on Scaled Down Fractal Tree Models of Major Urban Tree Species in Singapore. Forests. 11, 803 (2020). Zhao, X. L., Li, G. J., & Gao, T. Y. Thermal Comfort Effects and Morphological Characteristics of Typical Street Trees in Summer in Harbin. Chinese Journal of Landscape Architecture. 12, 74–80 (2016). Tables Table 1. Parameters of tree for simulation S cenarios Parameters of tree (m) Tree canopy morphologies Spheroid C one Inverted C one Cylinder E llipsoid C uboid S1 Height 8 Trunk height 2 DBH 0.25 Crown width 1, 2, 3, 4, 5, 6, 7, 8 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4 S2 Height 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10 Trunk height 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4 DBH 0.25 Crown width 6 3 S3 Height 8 Trunk height 2 Plant spacing of two trees 3, 6, 9, 12, 15, 18, 21 DBH 0.25 Crown width 6 3 Table 2. Downwind deceleration zones Zones Z0 Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9 Wind velocity ( m/s ) 3.12 -3.44 2.81 - 3.12 2.50 - 2.81 2.19 - 2.50 1.88 - 2.19 1.56 - 1 . 88 1.25 - 1.56 0.94 - 1.25 0.62 - 0.94 0.31 - 0.62 Colors in wind velocity distribution map Weight 1.516% 2.035% 2.841% 4.008% 5.638% 7.876% 10.941% 15.154% 20.991% 29.000% Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4905258","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":355917854,"identity":"7806fefc-1eb5-4834-a7dc-c09a2d2ef7f2","order_by":0,"name":"Lei Fan","email":"","orcid":"","institution":"Forestry College, Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Fan","suffix":""},{"id":355917855,"identity":"4b3ed36e-64f8-4c7a-b44d-c55ce67520e7","order_by":1,"name":"Hongzuo Jia","email":"","orcid":"","institution":"Forestry College, Shenyang Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Hongzuo","middleName":"","lastName":"Jia","suffix":""},{"id":355917856,"identity":"6de88e0a-3334-4a7d-8f03-a9c5dc08a9f3","order_by":2,"name":"Yan Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDACCQglB+UyE6/FmHQtiQ1Ea5Gf3XxMmqfmTvr8GcnPJBgqrBMb2M8ewKuFcc6xNGmeY89yN9xIM5NgOJOe2MCTl4BXC7NEjpk0D9vh3A0SCWYSjG2HExskeAzwamEDa/l3OF1+Rvo3CcZ/RGjhAWnhbTucwHAjB2hLAxFaJCTSki3n9h023HDmTbFFwrF04zaeHPxa5GckH7zx5tthefn29I03PtRYy/azn8GvBQSYeECkQAIDQwLIdwTVAwHjDxDJf4AYtaNgFIyCUTASAQDdoECkFeSpHgAAAABJRU5ErkJggg==","orcid":"","institution":"Forestry College, Shenyang Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2024-08-13 08:14:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4905258/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4905258/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64918281,"identity":"45c14abf-3d75-4df9-9452-a9e32d0c46e9","added_by":"auto","created_at":"2024-09-20 11:11:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47839,"visible":true,"origin":"","legend":"\u003cp\u003eTree canopy morphologies\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/45d6889a06db6b1a7ff6b7ad.png"},{"id":64919641,"identity":"f2b6738e-b83e-4cd7-8f63-1f9f6456ecc8","added_by":"auto","created_at":"2024-09-20 11:27:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48692,"visible":true,"origin":"","legend":"\u003cp\u003eWind velocity distribution map of varying crown width (Spheroid)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/01a15366f42d64cb052457c6.png"},{"id":64918926,"identity":"2a63cb3f-717d-48dd-8f45-c43d28621c5c","added_by":"auto","created_at":"2024-09-20 11:19:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119325,"visible":true,"origin":"","legend":"\u003cp\u003eThe linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e / AZ with crown width\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/ad348f3e8e1142d4d8117ddb.png"},{"id":64918289,"identity":"101c1723-27cc-4562-90f2-8c9ba5d9a0d1","added_by":"auto","created_at":"2024-09-20 11:11:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":114350,"visible":true,"origin":"","legend":"\u003cp\u003eThe linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e / AZ with trunk height\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/2ce6db3738d1d540b4873923.png"},{"id":64918286,"identity":"16da848a-16da-48b1-ae08-42091180e2ea","added_by":"auto","created_at":"2024-09-20 11:11:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":109008,"visible":true,"origin":"","legend":"\u003cp\u003eThe linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e / AZ with plant spacing\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/d390bc3548fcea71e470abde.png"},{"id":64918927,"identity":"7f4d590c-7a72-4145-ae4a-f0f18c6963e5","added_by":"auto","created_at":"2024-09-20 11:19:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":118186,"visible":true,"origin":"","legend":"\u003cp\u003eThe linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e with AZ\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/e295be0ab12135a9b2e10f7d.png"},{"id":64918283,"identity":"80b0e065-636c-4aaf-a583-a84b14a9f3c0","added_by":"auto","created_at":"2024-09-20 11:11:22","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":105660,"visible":true,"origin":"","legend":"\u003cp\u003eThe linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e with AZ\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/dc9d05684183286eefb090cd.png"},{"id":66108760,"identity":"dee94b74-54b8-4cd4-a36c-bdfb1bb838a0","added_by":"auto","created_at":"2024-10-07 19:46:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1196485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/5757d1a4-dac2-4b91-80d9-3c9fe7569db7.pdf"},{"id":64918928,"identity":"70ee1f19-55e2-4397-861e-8d8073aa476c","added_by":"auto","created_at":"2024-09-20 11:19:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2775397,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4905258/v1/5ff137987563cf7aa1dd3219.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predicting the influence of trees on wind environment in pedestrian-level through numerical simulation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWind is an important component of atmospheric environment. Wind environment is closely related to people's lives and has a great influence on the comfort and safety of the environment. Suitable wind speed and ventilation are conducive to the diffusion of atmospheric pollutants, reduce urban heat island effect, improve urban air quality, and improve the thermal comfort of outdoor activities\u003csup\u003e1\u0026ndash;5\u003c/sup\u003e. However, with the continuous urbanization, the appearance of a large number of artificial structures has affected the urban wind speed, wind direction and ventilation efficiency, which further worsens the urban heat island effect and air pollution\u003csup\u003e6\u003c/sup\u003e. In recent decades, the pedestrian\u0026rsquo;s outdoor thermal comfort has been critical for designing sustainable cities, which can be affected by wind flow in urban spaces\u003csup\u003e4, 7\u003c/sup\u003e. Wind speed, an important factor impacting thermal comfort, has been shown to have various impacts on pedestrians depending on the specific surrounding conditions\u003csup\u003e8\u0026ndash;11\u003c/sup\u003e. Pedestrian-level wind environment in urban areas has a significant impact on the quality of urban dwellers' outdoor thermal comfort\u003csup\u003e3, 12\u003c/sup\u003e. The analysis and optimization of pedestrian-level wind environment is of great significance for improving urban living environment and constructing sustainable urban space. And therefore, the pedestrian-level wind environment has attracted the attention of academics.\u003c/p\u003e \u003cp\u003eGiven the growing call for more vegetation in cities, it is important to study the wind resistant of urban trees in order to address outdoor natural ventilation problem in the landscape planning\u003csup\u003e13\u003c/sup\u003e. Previous studies have shown trees are more effective climate moderators than the other green elements\u003csup\u003e14\u0026ndash;16\u003c/sup\u003e. Trees have always played a crucial role for human beings, providing several ecosystem services in urban areas. It can regulate the local microclimate environment of the city, alleviate the heat island effect, hinder and adsorb the particulate pollutants, absorb the gaseous pollutants and so on\u003csup\u003e17\u0026ndash;21\u003c/sup\u003e. And the trees can alter the thermal-stress conditions by reducing wind-speed, changing wind-directions, and improving the comfort and health of the wind environment\u003csup\u003e22\u0026ndash;28\u003c/sup\u003e. The main methods used to study the flow field around trees include in situ measurements, wind tunnel tests and numerical simulations. In recent years, the airflow field around trees has been widely simulated using Computational Fluid Dynamics (CFD) technology\u003csup\u003e9, 22, 29\u0026ndash;30\u003c/sup\u003e. However, in most urban construction activities, designers only estimate whether the urban space in the scheme can meet the requirements of ventilation in summer and windproof in winter based on experience, and habitually use plants in aesthetic design and vertical design, but ignore their important role in improving wind environment, and there is a lack of assessment studies on the influence factors of trees on wind environment. Therefore, it is necessary to have a comprehensive understanding of the changing laws of the flow field around trees to guide urban tree planting, which is of great practical significance for building a comfortable and healthy urban wind environment, creating a liveable urban ecological environment and achieving sustainable urban development.\u003c/p\u003e \u003cp\u003eThere are many studies on wind environment based on tree characteristics. Zheng's study show that tree crowns, created by branches, leaves and twigs, can provide shade and reduce wind speed\u003csup\u003e31\u003c/sup\u003e. Lai et al.\u003csup\u003e32\u003c/sup\u003e found that the wind load a tree withstood is mainly applied to its crown, whose morphology and structure directly affect the degree of wind load given a certain wind condition. Cao et al.\u003csup\u003e33\u003c/sup\u003e and Zhang et al.\u003csup\u003e34\u003c/sup\u003e analyzed the relationships between changes in tree characteristics and wind speed, such as crown displacement, windward area and porosity. Mayaud et al. investigated the effects of a single tree, a grass clump, and a shrub on turbulent wind flow and discovered that wind velocity can be reduced by up to 70% in the lee of vegetation\u003csup\u003e35\u003c/sup\u003e. Amani-Beni et al. have investigated the effects of wind loading on three dimensional tree models using numerical simulation with implications for urban design\u003csup\u003e36\u003c/sup\u003e. In some papers, the wind environment is studied by taking individual trees as examples. Five-year-old white fir trees (\u003cem\u003eAbides concolor\u003c/em\u003e) were tested as the wind break model in Lee and Lee\u0026rsquo;s work\u003csup\u003e23\u003c/sup\u003e. The drag coefficients of four common subtropical trees (\u003cem\u003eFicus microcarpa\u003c/em\u003e, \u003cem\u003eMangifera indica\u003c/em\u003e, \u003cem\u003eMichelia alba\u003c/em\u003e and \u003cem\u003eBauhinia blakeana\u003c/em\u003e) have been obtained by using wind tunnel measurements\u003csup\u003e37\u003c/sup\u003e. The overall airflow variation in the downwind zone of a single tree is usually represented by the airflow variation in the central axis of the tree, based on which studies have developed airflow field models around single plants\u003csup\u003e35, 38\u003c/sup\u003e. Some scholars are also very concerned wind speed on the leeward side of trees: Zeng et al. point out the trees can cause a decrease in wind speed on their leeward side and limit heat dissipation\u003csup\u003e28\u003c/sup\u003e. Cheng et al. found out the downwind deceleration zone based on the trend of wind speed in their experiments\u003csup\u003e38\u003c/sup\u003e. For wind environmental improvements, the tree species selection and arrangement is the important parameters to be considered by planners and designers. So it is worth to be investigated for a better understanding of the wind environment which determine pedestrian comfort. The analysis of wind behavior behind trees has become an important task to address at the planning stage of tree planting. Raman et al. pointed out that isolated trees are found providing better cooling than the loosely clustered ones, containing open spaces in between\u003csup\u003e39\u003c/sup\u003e. Single tree is the basic unit of urban green layouts. Different types of green layout can be formed by planting multiple single trees together. In order to research the effect of green layouts on wind environment, it is necessary to study the wind environment of single tree. However, the wind environment of single tree is still not fully understood, especially from the point of view of tree canopy morphologies.\u003c/p\u003e \u003cp\u003eThe complexity of the architecture of plant canopies makes the flow phenomena within and around the canopies extremely complex and difficult to predict\u003csup\u003e40\u003c/sup\u003e. Many factors can affect wind mitigation including wind direction, tree type, stem height, tree height, trunk height, crown width, distance between trees\u003csup\u003e41\u0026ndash;42\u003c/sup\u003e. In order to figure out how crown width, trunk heights, and plant spacing of single tree influence the wind velocity, the PHOENICS CFD numerical simulation was performed in this study. Through the study of varying canopy morphologies of trees, to obtain downwind speeds data of the pedestrian-level. The goal of the present work is threefold: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) to explore the influence of crown width, trunk height and plant spacing on wind velocity; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) to calculate the area of downwind deceleration zones of varying crown width, trunk height above ground, and plant spacing; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) to find out the relationship between the influence of trees on wind (wind velocity and downwind deceleration zones) and varying tree\u0026rsquo;s parameters.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy area.\u003c/strong\u003e Shenyang is located in the south of northeast China and the middle of Liaoning Province. It is the capital city of Liaoning Province and the central hub city of Central Liaoning City Group, the seventh largest city group in China. It is located at 41.80\u0026deg; North Latitude and 123.43\u0026deg; East Longitude and has a total area of 12,948 km\u003csup\u003e2\u003c/sup\u003e. Shenyang is located in the monsoon area with high frequency and strong wind, which brings many negative effects to the daily life of city residents. The rapid urbanization has an influence on the climatic environment of Shenyang, especially the wind and thermal environment in the central urban area. As a result, the urban heat island effect is enhanced in Shenyang in summer, and haze weather often occurs in winter heating period, which greatly affects the daily life and health of urban residents\u003csup\u003e43,44\u003c/sup\u003e. In this paper, trees planted in Shenyang Agricultural University were selected as reference for numerical simulation of plant parameters. According to the survey data, there are 62 species of trees in Shenyang Agricultural University. The main tree species are \u003cem\u003eAbies nephrolepis\u003c/em\u003e, \u003cem\u003ePicea koraiensis\u003c/em\u003e, \u003cem\u003eLarix kaempferi\u003c/em\u003e, \u003cem\u003ePinus koraiensis\u003c/em\u003e, \u003cem\u003ePinus tabuliformis\u003c/em\u003e, \u003cem\u003eJuniperus chinensis\u003c/em\u003e, \u003cem\u003eTaxus cuspidata\u003c/em\u003e, \u003cem\u003eRobinia pseudoacacia\u003c/em\u003e, \u003cem\u003eGleditsia japonica\u003c/em\u003e, \u003cem\u003eAcer truncatum\u003c/em\u003e, \u003cem\u003eQuercus mongolica\u003c/em\u003e, \u003cem\u003eGinkgo biloba\u003c/em\u003e, \u003cem\u003eSophora japonica\u003c/em\u003e, \u003cem\u003ePrunus davidiana\u003c/em\u003e, \u003cem\u003ePrunus padus\u003c/em\u003e, \u003cem\u003eSalix matsudana\u003c/em\u003e, \u003cem\u003eSalix babylonica\u003c/em\u003e, \u003cem\u003eJuglans mandshurica\u003c/em\u003e, \u003cem\u003ePopulus alba\u003c/em\u003e, \u003cem\u003eSophora japonica\u003c/em\u003e, \u003cem\u003eCatalpa ovata\u003c/em\u003e, \u003cem\u003eUlmus pumila\u003c/em\u003e, \u003cem\u003eFraxinus mandshurica\u003c/em\u003e, and \u003cem\u003eSyringa reticulata\u003c/em\u003e. These tree species have strong adaptability and good growth characteristics, and are widely used in urban greening.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNumerical Simulation by PHOENICS.\u003c/strong\u003e In this paper, PHOENICS is selected to simulate the effect of trees on wind environment. \u003cem\u003eEcological Housing Technology Assessment Manual of China\u003c/em\u003e (2003) stipulates that at the pedestrian height, that is, 1.5 m above the surface, the wind speed can only be considered comfortable when it is less than 5 m/s, and it cannot be considered comfortable when it exceeds this value\u003csup\u003e45\u003c/sup\u003e. \u003cem\u003eAssessment Standard for Green Building of China\u003c/em\u003e stipulates that the wind speed in the pedestrian area around the building should be less than 5m/s\u003csup\u003e46\u003c/sup\u003e. In addition, the studies also found that people\u0026apos;s sitting, standing and walking behaviors are relatively comfortable when the ambient wind speed is between 0\u0026minus;5.0m/s, while people feel uncomfortable when the ambient wind speed exceeds 5m/s\u003csup\u003e7\u003c/sup\u003e. Therefore, the inlet wind speed of simulation is set at 5m/s. At present, two equation models, k-\u0026epsilon; model and RNG k-\u0026epsilon; model, are the most widely used in the numerical simulation of outdoor wind environment. The simulation results of these two models are close to the actual wind field\u003csup\u003e47\u003c/sup\u003e. Among them, the overall accuracy of RNG k-\u0026epsilon; model is higher, and is chosen for the study of this paper. In this study, the calculation area is set as 210m\u0026times;210m\u0026times;50m, the tree is located in the center of the calculation area, the inlet wind direction is set as N, and the inlet wind speed is 5m/s.\u003c/p\u003e\n\u003cp\u003ePrevious studies have simplified tree canopies into ellipsoid, cone, cylinder, cuboid, square, rectangular and other geometries to analyze the effect of trees on the flow field\u003csup\u003e48,49\u003c/sup\u003e. Liu et al. stated that a better understanding of the airflow around a single plant is fundamental and important in the study of the flow field across multiple plants \u003csup\u003e48\u003c/sup\u003e. Based on the tree species in site investigation, tree canopy morphologies were simplified into six types in this paper: Spheroid, Cone, Inverted Cone, Cylinder, Ellipsoid, and Cuboid (Fig. 1). In the early period, the tree parameters of Shenyang Agricultural University were measured and found that the tree average height of 8 m accounted for a large proportion of trees, and the average DBH was 0.25m. Therefore, in the simulation experiment, the height of a single tree was set to 8 m, and the DBH was set to 0.25m. The 3D plant modeling is carried out by using Rhino software. Then the model is imported into PHOENICS and the canopy model parameters are set as \u0026quot;porous media parameter module FOLIAGE\u0026quot;, regardless of the internal structure of the canopies. This paper explores three scenarios of the influence of trees on wind environment (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). S1 (48 sub-scenarios): The tree height, trunk height, and DBH are set to fixed value, so as to explore the influence of varying crown widths on wind velocity; S2 (54 sub-scenarios): The DBH and crown width are set to fixed value, so as to explore the influence of varying trunk heights on wind velocity; S3 (42 sub-scenarios): The tree height, trunk height, DBH, and crown width are set to fixed value, so as to explore the influence of varying plant spacing of two trees on wind velocity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThrough numerical simulation, wind velocity distribution map of varying scenarios can be obtained (Fig.\u0026nbsp;2). The map can show the effect of trees on wind velocity weakening and direction changing. In order to describe the pedestrian-level influence trend of trees on wind, wind velocity distribution map is divided into 10 levels of downwind deceleration zones\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ0, Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, Z9 (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). A range from Z0 to Z9 indicates that the trees is weakening the wind velocity more and more, so the weights Z0 to Z9 are calculated using Analytic Hierarchy Process. The downwind deceleration zones have a elliptical shape from the top view. This study used Photoshop histograms to calculate the pixels of each Zn and then converted to the area. According to the area and weight of Zn, the influence value of trees on wind velocity (IF\u003csub\u003ewind\u003c/sub\u003e) in each scenario was calculated.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"690\" height=\"27\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere \u003cem\u003eZn\u003c/em\u003e is the area of downwind deceleration zone, \u003cem\u003eW\u003c/em\u003e\u003csub\u003e\u003cem\u003eZn\u003c/em\u003e\u003c/sub\u003e is the weight of the downwind deceleration zone.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eInfluence of crown widths on wind velocity.\u003c/b\u003e According to the wind velocity distribution maps, with the increase of crown width, there was a strong positive correlation between crown width and IF\u003csub\u003ewind\u003c/sub\u003e (Fig.\u0026nbsp;3a). Among them, Ellipsoid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.98848) is the strongest correlation between crown width and IF\u003csub\u003ewind\u003c/sub\u003e, while Cylinder (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.90431) is the weakest. On the whole, the min IF\u003csub\u003ewind\u003c/sub\u003e appeared at 1m (0.5 m) crown width and the max IF\u003csub\u003ewind\u003c/sub\u003e appeared at 8m (4.0 m) crown width. When the crown width is 1m (0.5 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 0.02 (Cone) to 0.60 (Cuboid); crown width is 2m (1.0 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 4.43 (Inverted Cone) to 9.87 (Spheroid); crown width is 3 m (1.5 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 2.19 (Cuboid) to 12.09 (Cylinder); crown width is 4 m (2.0 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 11.19 (Cone) to 16.86 (Cylinder); crown width is 5m (2.5 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 17.08 (Cone) to 35.70 (Cylinder); crown width is 6m (3.0 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 24.59 (Ellipsoid) to 36.03 (Spheroid); crown width is 7 m (3.5 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 30.66 (Ellipsoid) to 58.32 (Spheroid); crown width is 8 m (4.0 m), IF\u003csub\u003ewind\u003c/sub\u003e ranges from 35.08 (Ellipsoid) to 76.24 (Spheroid).\u003c/p\u003e \u003cp\u003eAccording to the wind velocity distribution maps. Wherever each sub-scenario contains several downwind deceleration zones, these zones are continuous. There was a strong positive correlation between crown width and the area of downwind deceleration zones (AZ) (Fig.\u0026nbsp;3b). Linear relationship analysis model shows that the strongest positive correlation between crown width and AZ is Ellipsoid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.99054), and the weakest is Cylinder (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.78106). On the whole, the min AZ appeared at 1 m (0.5 m) crown width and the max AZ appeared at 8 m (4.0 m) crown width. When the crown width is 1 m (0.5 m), AZ ranges from 0.96 m\u003csup\u003e2\u003c/sup\u003e (Cone) to 39.87 m\u003csup\u003e2\u003c/sup\u003e (Cuboid); crown width is 2 m (1.0 m), AZ ranges from 215.02 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 462.95 m\u003csup\u003e2\u003c/sup\u003e (Spheroid); crown width is 3 m (1.5 m), AZ ranges from 73.02 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 372.17 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid); crown width is 4 m (2.0 m), AZ ranges from 248.54 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 617.64 m\u003csup\u003e2\u003c/sup\u003e (Inverted Cone); crown width is 5 m (2.5 m), AZ ranges from 352.49 m\u003csup\u003e2\u003c/sup\u003e (Cone) to 631.16 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); crown width is 6 m (3.0 m), AZ ranges from 475.16 m\u003csup\u003e2\u003c/sup\u003e (Cylinder) to 1128.13 m\u003csup\u003e2\u003c/sup\u003e (Inverted Cone); crown width is 7 m (3.5 m), AZ ranges from 607.49 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 1766.09 m\u003csup\u003e2\u003c/sup\u003e (Inverted Cone); crown width is 8 m (4.0 m), AZ ranges from 784.52 m\u003csup\u003e2\u003c/sup\u003e (Cylinder) to 2084.62 m\u003csup\u003e2\u003c/sup\u003e (Inverted Cone).\u003c/p\u003e \u003cp\u003e \u003cb\u003eInfluence of trunk heights on wind velocity.\u003c/b\u003e Wind velocity distribution maps show that with the increase of trunk height, the corresponding IF\u003csub\u003ewind\u003c/sub\u003e value also changes. Trunk heights of Spheroid, Cone, Cylinder, Ellipsoid, and Cuboid are negatively correlated with IF\u003csub\u003ewind\u003c/sub\u003e values (Fig.\u0026nbsp;4a). Among them, Spheroid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.94455) is the strongest correlation between trunk height and IF\u003csub\u003ewind\u003c/sub\u003e, while Cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.01252) is the weakest. Trunk height of Inverted Cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.83173) is positively correlated with IF\u003csub\u003ewind\u003c/sub\u003e values. For every tree canopy morphology, the distribution of min and max IF\u003csub\u003ewind\u003c/sub\u003e is irregular. When the trunk height is 0.0 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 7.01 (Cuboid) to 42.21 (Cylinder); trunk height is 0.5 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 6.06 (Cuboid) to 47.24 (Cylinder); trunk height is 1.0 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 4.64 (Cuboid) to 51.72 (Cylinder); trunk height is 1.5 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 2.69 (Cuboid) to 37.01 (Cylinder); trunk height is 2.0 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 2.24 (Cuboid) to 33.92 (Cylinder); trunk height is 2.5 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 1.44 (Cuboid) to 30.41 (Cylinder); trunk height is 3.0 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 0.37 (Cuboid) to 25.43 (Cylinder); trunk height is 3.5 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 0 (Cuboid) to 26.23 (Cone); trunk height is 4.0 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 0 (Cuboid) to 25.55 (Cone).\u003c/p\u003e \u003cp\u003eAccording to the wind velocity distribution maps, the AZ changes with the increase of trunk height. Trunk heights of Inverted cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.96664), Cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.71474), and Cylinder (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.07178) are positively correlated with AZ (Fig.\u0026nbsp;4b). Trunk heights of Cuboid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.90109), Spheroid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.48754), and Ellipsoid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.43103) are negatively correlated with AZ. For every tree canopy morphology, the distribution of min and max AZ is irregular. When the trunk height is 0.0 m, AZ ranges from 163.63 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 377.36 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); trunk height is 0.5 m, AZ ranges from 164.13 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 450.25 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 1.0 m, AZ ranges from 162.37 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 499.05 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 1.5 m, AZ ranges from 157.36 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 507.28 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 2.0 m, AZ ranges from 142.14 m\u003csup\u003e2\u003c/sup\u003e (Cuboid)\u0026thinsp;~\u0026thinsp;601.64 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 2.5 m, AZ ranges from 95.06 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 556.33 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 3.0 m, AZ ranges from 24.47 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 544.26 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 3.5 m, AZ ranges from 0 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 615.00 m\u003csup\u003e2\u003c/sup\u003e (Cone); trunk height is 4.0 m, AZ ranges from 0 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 587.33 m\u003csup\u003e2\u003c/sup\u003e (Cone).\u003c/p\u003e \u003cp\u003e \u003cb\u003eInfluence of plant spacing on wind velocity.\u003c/b\u003e Wind velocity distribution maps show that with the increase of plant spacing, the corresponding IF\u003csub\u003ewind\u003c/sub\u003e value also changes. Plant spacing of Inverted cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.20524), Spheroid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.18993), and Cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.03381) are positively correlated with IF\u003csub\u003ewind\u003c/sub\u003e values (Fig.\u0026nbsp;5a). Plant spacing of Ellipsoid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.60740), Cylinder (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.11324), and Cuboid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.03384) are negatively correlated with IF\u003csub\u003ewind\u003c/sub\u003e values. For every tree canopy morphology, the distribution of min and max IF\u003csub\u003ewind\u003c/sub\u003e is irregular. When the plant spacing is 3 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 7.06 (Ellipsoid) to 18.16 (Cylinder); plant spacing is 6 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 8.77 (Ellipsoid) to 24.22 (Cylinder); plant spacing is 9 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 7.51 (Ellipsoid) to 20.81 (Cylinder); plant spacing is 12 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 7.36 (Ellipsoid) to 19.89 (Cylinder); plant spacing is 15 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 6.52 (Ellipsoid) to 19.42 (Cylinder); plant spacing is 18 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 5.38 (Ellipsoid) to 19.32 (Cylinder); plant spacing is 21 m, IF\u003csub\u003ewind\u003c/sub\u003e ranges from 5.84 (Ellipsoid) to 19.01 (Cylinder).\u003c/p\u003e \u003cp\u003eWind velocity distribution maps show that a two-tailed feature appears in downwind deceleration zones. The AZ increased first and then decreased with the increase of planting spacing. Plant spacing of Cylinder (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.83393), Spheroid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.56241), Inverted cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.33146), Cone (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.24663), and Cuboid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.11994) are positively correlated with AZ (Fig.\u0026nbsp;5b). Plant spacing of Ellipsoid (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.33901) are negatively correlated with AZ. For every tree canopy morphology, the distribution of min and max AZ is irregular. When the plant spacing is 3 m, AZ ranges from 201.35 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 367.82 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 6 m, AZ ranges from 269.25 m\u003csup\u003e2\u003c/sup\u003e (Cuboid) to 461.37 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 9 m, AZ ranges from 243.10 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 478.14 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 12 m, AZ ranges from 241.17 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 506.31 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 15 m, AZ ranges from 212.48 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 529.94 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 18 m, AZ ranges from 182.06 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 547.07 m\u003csup\u003e2\u003c/sup\u003e (Cylinder); plant spacing is 21 m, AZ ranges from 188.62 m\u003csup\u003e2\u003c/sup\u003e (Ellipsoid) to 540.79 m\u003csup\u003e2\u003c/sup\u003e (Cylinder).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn order to concretize and digitally present the wind environment at the pedestrian-level, this paper conducted a numerical simulation study on six canopy morphologies of trees in multi-scenarios. It is found that the changes of wind velocity and downwind deceleration zones influence by trees. The IF\u003csub\u003ewind\u003c/sub\u003e and AZ values of trees with varying crown width, trunk height and plant spacing have obvious differences.\u003c/p\u003e \u003cp\u003eThe influence of plants on the pedestrian level wind environment is the focus of scholars\u003csup\u003e8,9,10,11,50,51,52\u003c/sup\u003e. Visualization and parameterization of tree canopy morphologies is the basic setting of these researches\u003csup\u003e53,54\u003c/sup\u003e. In this paper, the simulation experiments of six canopy morphologies have enriched the types of similar numerical simulation of tree canopy shape. The wind environment simulation research on the whole green space shows the overall situation of wind environment\u003csup\u003e15, 20\u003c/sup\u003e, but the wind environment of \"single tree\", the basic element of green space, is still an important topic. The numerical characteristics of single tree wind environment need to be solved fundamentally for the diversified planting forms of greening. It is necessary to numeralize the wind environment of the tree, so as to further quantify the influence of the tree on wind velocity. Based on previous studies, this paper designed three scenarios (S1, S2, and S3), including 144 sub-scenarios, to simulate the pedestrian-level wind environment of individual trees and coupled planting. Wind velocity distribution map shows 10 sub-zones (Fig.\u0026nbsp;2), all of which are downwind deceleration zones\u003csup\u003e27\u003c/sup\u003e. According to the area of the sub-zones and the corresponding weight, the IF\u003csub\u003ewind\u003c/sub\u003e of the scenario can be calculated. This is different from the expression in previous studies, which used the multiple of tree height to represent the length of wind speed zone, while this paper used the area to represent\u003csup\u003e27\u003c/sup\u003e. \"IF\u003csub\u003ewind\u003c/sub\u003e\" is a new term proposed in this paper, which is intended to explain the influence of trees on wind velocity reduction in a quantitative way. In the experiment, the IF\u003csub\u003ewind\u003c/sub\u003e of six canopy morphologies changed with the varying of crown width, trunk height and plant spacing.\u003c/p\u003e \u003cp\u003eThe focus of this paper is to use PHOENICS to simulate the effects of crown width (S1), trunk height (S2) and plant spacing (S3) on wind velocity. To interpret, the findings suggest that for the same tree canopy morphology, the crown width had a strong positive correlation with both IF\u003csub\u003ewind\u003c/sub\u003e and AZ. With the increase of tree crown width, the corresponding IF\u003csub\u003ewind\u003c/sub\u003e and AZ increased (Fig.\u0026nbsp;6a). Compared with previous studies, it is found that the influence of different canopy size on wind velocity is of more practical significance, thus supporting the selection of suitable crown width according to different wind speed reduction needs, which is more targeted. In addition, the trunk height is negatively correlated with the IF\u003csub\u003ewind\u003c/sub\u003e value, which is the same as the research result of Zhao et al. \"There is a significant negative correlation between the trunk height from the ground and the wind environment\"\u003csup\u003e55\u003c/sup\u003e, but the Inverted Cone canopy morphology in this paper is positively correlated with the IF\u003csub\u003ewind\u003c/sub\u003e value (Fig.\u0026nbsp;4a), which can be used as a supplement to this theory. The correlation between trunk height and AZ value was observed in two cases: the positive correlations are Cone, Inverted Cone, and Ellipsoid; the negative correlations are Spheroid, Cylinder, and Cuboid. However, whether the correlation is positive or negative, the maximum value of AZ appears in the median range of the trunk height (Fig.\u0026nbsp;6b): Spheroid (1.5m), Cone (3.5m), Inverted Cone (3.5m), Cylinder (2.0m), Ellipsoid (2.5m), and Cuboid (0.5m); The minimum value of AZ appears when the plant spacing is the largest or the smallest: Spheroid (4.0m), Cone (0.0m), Inverted Cone (0.0m), Cylinder (0.0m), Ellipsoid (3.5m), and Cuboid (4m). The Numerical simulation results of crown width and trunk height same to the results of Hosseinzadeh and Keshmiri\u0026rsquo;s\u003csup\u003e51\u003c/sup\u003e viewpoint \"Younger trees with crowns closer to the ground mitigate wind more. However, older trees with wider crowns are able to decrease wind more.\u0026rdquo; It also coincides with to the discussion of Huang et al.\u003csup\u003e19\u003c/sup\u003e \"the trunk height affects significantly the flow\". Finally, the correlation between plant spacing and IF\u003csub\u003ewind\u003c/sub\u003e value is also in two cases: Spheroid, Cone, and Inverted Cone are positively correlated with IF\u003csub\u003ewind\u003c/sub\u003e; Cylinder, Ellipsoid, and Cuboid are negatively correlated with IF\u003csub\u003ewind\u003c/sub\u003e. The reason is caused by the influence of the wind environment generated by the canopy morphologies. However, they have a common feature, that is, the maximum value of IF\u003csub\u003ewind\u003c/sub\u003e appears in the median range of plant spacing: Spheroid (9m), Cone (6m), Inverted Cone (15m), Cylinder (6m),\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ea - IF\u003csub\u003ewind\u003c/sub\u003e with crown width\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003es - IF\u003csub\u003ewind\u003c/sub\u003e with trunk height\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ec- IF\u003csub\u003ewind\u003c/sub\u003e with plant spacing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFigure 6.\u003c/b\u003e The linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e with AZ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEllipsoid (6m), and Cuboid (12m) (Fig.\u0026nbsp;6c). Most of the minimum values of IF\u003csub\u003ewind\u003c/sub\u003e occur when the plant spacing is closest or farthest: Spheroid (3m), Cone (3m), Inverted Cone (3m), Cylinder (3m), Ellipsoid (18m), and Cuboid (21m). Plant spacing is positively correlated with AZ values, except for Ellipsoid.\u003c/p\u003e \u003cp\u003eAlthough this paper presupposes 10 downwind deceleration zones, only Cuboid's trunk height at 0.0 m, 0.5 m, and 1.0 m includes all zones. The simulation results of other scenarios include only 1\u0026ndash;9 zones. The findings seems indicate that no matter how many zones are included in the sub-scenario, these zones are continuous, and there is no disconnection of zones\u0026rsquo; serial number. Moreover, in most cases, the area of these zones is progressively reduced as the serial number increases. When Cuboid had trunk heights of 0.0 m, 0.5 m, and 1.0 m, their ability to reduce wind velocity reached 87.6%, exceeding that of Mayaud et al.\u003csup\u003e35\u003c/sup\u003e stated \"that wind velocity can be reduced by up to 70% in the lee of vegetation\", which may explained by the differences in inlet wind speed and canopy details.\u003c/p\u003e \u003cp\u003eThis paper focuses on the influences of crown width (S1), trunk height (S2) and plant spacing (S3) on wind velocity of single trees in pedestrian-level. The relationship between the varying parameters and the IF\u003csub\u003ewind\u003c/sub\u003e/AZ values was discussed. So is there a correlation between the AZ and IF\u003csub\u003ewind\u003c/sub\u003e? To further validate this question, a linear analysis was performed. The test results reveal that except for the trunk height and plant spacing scenarios of\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabg\" border=\"1\"\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ea - crown width\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb - trunk height\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ec- plant spacing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFigure 7.\u003c/b\u003e The linear regression model of the IF\u003csub\u003ewind\u003c/sub\u003e with AZ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCylinder, the AZ is positively correlated with IF\u003csub\u003ewind\u003c/sub\u003e in other scenarios (Fig.\u0026nbsp;7). Which provides additional evidence on the IF\u003csub\u003ewind\u003c/sub\u003e / AZ by trees.\u003c/p\u003e \u003cp\u003eBased on the above analysis, we can draw the following results: For most scenarios, the larger the canopy width, the larger its IF\u003csub\u003ewind\u003c/sub\u003e and AZ values; In case of the trunk height and planting spacing scenarios, both the IF\u003csub\u003ewind\u003c/sub\u003e and AZ have the maximum values, and after the maximum value appears, there is a trend of gradual decrease. The results show that the varying of crown width (S1), trunk height (S2) and plant spacing (S3) all have an influence on wind velocity, and the maximum and minimum values of IF\u003csub\u003ewind\u003c/sub\u003e and AZ as well as their changing trends are simulated. The influence of crown width on wind velocity is less influenced and limited by canopy morphology. However, the influence of trunk height and plant spacing on wind velocity is limited by crown morphology. Our research results enrich the canopy morphologies setting for numerical simulation of tree\u0026rsquo;s wind environment, and the influence of crown width, trunk height and plant spacing on wind environment also strongly prove our initial hypothesis. The conclusion of this study provides a reference for the diversified planting design of today.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research examines the influence of trees on wind environment t in pedestrian-level. By integrating the theories of CFD simulation method and trees benefits, six canopy morphology spatial models are proposed and validated. The PHOENICS is used for numerical simulation (144 scenarios), and the data are analyzed using Photoshop and linear regression model. It is found that crown width, trunk height, and plant spacing influence on wind velocity. Furthermore, our findings suggest that IF\u003csub\u003ewind\u003c/sub\u003e and AZ can represent the influence value of trees on wind velocity. Because the crown width, trunk height and plant spacing all have an influence on the two indicators. With the findings, our study makes several theoretical and practical contributions.\u003c/p\u003e \u003cp\u003eFirstly, the influence of trees on wind is linearly correlated with the varying crown width, trunk height and plant spacing. The influence of tree on wind velocity can be expressed by IF\u003csub\u003ewind\u003c/sub\u003e and AZ, where IF\u003csub\u003ewind\u003c/sub\u003e value indicates the wind reducing ability of tree; AZ value shows the area of downwind deceleration zones. This result enriches the wind environment theory of trees. More importantly, the crown morphology affects the tree\u0026rsquo;s influence on wind velocity. Because there were varying degrees of positive and negative linear correlations between IF\u003csub\u003ewind\u003c/sub\u003e and trunk height / plant spacing, and between AZ and trunk height / plant spacing. This finding to modify the detail theory of the negative linear correlation between trunk height / plant spacing and wind velocity. Except for the scenarios of Cylinder\u0026rsquo;s trunk height and plant spacing, the AZ values in other scenarios where the crown width, trunk height and plant spacing are all positively correlated with the IF\u003csub\u003ewind\u003c/sub\u003e values. Additionally, the findings indicates that no matter how many downwind deceleration zones are included in the scenarios, these zones are continuous, and there is no disconnection of zones\u0026rsquo; serial number. Moreover, in most cases, the area of these zones is progressively reduced as the serial number increases.\u003c/p\u003e \u003cp\u003eWe propose a new targeted wind velocity measurement system of trees developed using PHOENICS. The framework and the numerical simulation in this paper are intended to support and guide future studies of wind comfort and wind safety of trees in pedestrian-level, and to contribute to improved wind environmental quality in urban areas through reasonable tree planting. Our research results also provide relevant data reference for landscape architects and urban planners, and can provide numerical reference for the reasonably use of tree species with their IF\u003csub\u003ewind\u003c/sub\u003e and AZ. Which is of great practical significance for building a comfortable and healthy urban wind environment, creating a liveable urban ecological environment and achieving sustainable urban development. The numerical simulation experiment is an exploratory attempt. The simulation of wind velocity of tree is carried out in a ideal laboratory environment. There are some differences between the experimental results and the real environment. Therefore, in the follow-up study, it is necessary to modify and improve the simulation data combined with the field measured data.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe research was supported by Research Fund project of Liaoning Provincial Department of Education (JYTMS20231295), Social Science Research Fund project of Liaoning Province (L23BDJ002), University level Research Fund project of Shenyang Agricultural University (X2022005).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.F. and Y.Z. wrote the main manuscript text, and H. Z. J. prepared figures. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this article (and its supplementary information files).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eYang, L. \u0026amp; Li, Y. Thermal conditions and ventilation in an ideal city model of Hong Kong. Energ. Buildings. 43 (5), 1139\u0026ndash;1148 (2011).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePriyadarsini, R., Hien, W. N. \u0026amp; David, C. K. W. Microclimatic modeling of the urban thermal environment of Singapore to mitigate urban heat island. Sol. Energy. 82 (8), 727\u0026ndash;745 (2008).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eShui, T. T. et al. Assessment of pedestrian-level wind conditions in severe cold regions of China. Build. 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Numerical study on flow field and pollutant dispersion in an ideal street canyon within a real tree model at different wind velocities. Comput. Math. Appl. 81, 679\u0026ndash;692 (2021).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eChan, W. L. et al. Wind Loading on Scaled Down Fractal Tree Models of Major Urban Tree Species in Singapore. Forests. 11, 803 (2020).\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eZhao, X. L., Li, G. J., \u0026amp; Gao, T. Y. Thermal Comfort Effects and Morphological Characteristics of Typical Street Trees in Summer in Harbin. Chinese Journal of Landscape Architecture. 12, 74\u0026ndash;80 (2016).\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eParameters of tree for simulation\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"650\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.615384615384615%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003cstrong\u003ecenarios\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.923076923076923%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters of tree (m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.46153846153847%\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eTree canopy morphologies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.274463007159904%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpheroid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.785202863961814%\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.627684964200476%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInverted\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCylinder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.809069212410503%\"\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003cstrong\u003ellipsoid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.990453460620525%\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003euboid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.615384615384615%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.923076923076923%\"\u003e\n \u003cp\u003eHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.46153846153847%\" colspan=\"6\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eTrunk height\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eDBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eCrown width\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.29948364888124%\" colspan=\"4\"\u003e\n \u003cp\u003e1, 2, 3, 4, 5, 6, 7, 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.817555938037867%\" colspan=\"2\"\u003e\n \u003cp\u003e0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.615384615384615%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.923076923076923%\"\u003e\n \u003cp\u003eHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.46153846153847%\" colspan=\"6\"\u003e\n \u003cp\u003e6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eTrunk height\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eDBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eCrown width\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.29948364888124%\" colspan=\"4\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.817555938037867%\" colspan=\"2\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.615384615384615%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.923076923076923%\"\u003e\n \u003cp\u003eHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"64.46153846153847%\" colspan=\"6\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eTrunk height\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003ePlant spacing\u0026nbsp;of\u0026nbsp;two trees\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e3,\u0026nbsp;6,\u0026nbsp;9,\u0026nbsp;12,\u0026nbsp;15,\u0026nbsp;18,\u0026nbsp;21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eDBH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"72.1170395869191%\" colspan=\"6\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.882960413080895%\"\u003e\n \u003cp\u003eCrown width\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"46.29948364888124%\" colspan=\"4\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.817555938037867%\" colspan=\"2\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDownwind deceleration zones\u003c/p\u003e\n\u003ctable style=\"width: 4.9e+2pt;border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:105.45pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZones\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:37.4pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ0\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.65pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ1\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:37.85pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ2\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ3\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ4\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:37.85pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ5\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ6\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ7\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:37.85pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ8\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:39.25pt;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:#AEAAAA;padding:0in 0in 0in 0in;height:11.35pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:12.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eZ9\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:105.45pt;border:none;padding:0in 0in 0in 0in;height:22.7pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003eWind velocity (\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003em/s\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:37.4pt;border:none;padding:0in 0in 0in 0in;height:22.7pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family: \"Times New Roman\",serif;color:black;'\u003e3.12\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family: \"Times New Roman\",serif;color:black;'\u003e-3.44\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.65pt;border:none;padding:0in 0in 0in 0in;height:22.7pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e2.81\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e-\u003c/span\u003e\u003cspan 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style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e2.19\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e-\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;'\u003e2.50\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:38.25pt;border:none;padding:0in 0in 0in 0in;height:22.7pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:0in;margin-left:0in;text-align:center;line-height:10.0pt;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cspan 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\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4905258/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4905258/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWind environment is closely related to people's lives and has a great influence on the comfort and safety of the environment. This research examines the influence of trees on wind environment in pedestrian-level. By integrating the theories of CFD simulation method and trees benefits, six canopy morphologies (Spheroid, Cone, Inverted Cone, Cylinder, Ellipsoid, Cuboid) models are proposed and validated. The PHOENICS is used for numerical simulation (144 scenarios), and the data are analyzed using Photoshop and linear regression model. It is found that the influence of trees on wind is linearly correlated with the varying crown width, trunk height and plant spacing. The influence of tree on wind velocity can be expressed by IF\u003csub\u003ewind\u003c/sub\u003e (the wind reducing ability) and AZ (the area of downwind deceleration zones). The framework and the numerical simulation in this paper are intended to support and guide future studies of wind comfort and wind safety of trees in pedestrian-level, and to contribute to improved wind environmental quality in urban areas through reasonable tree planting.\u003c/p\u003e","manuscriptTitle":"Predicting the influence of trees on wind environment in pedestrian-level through numerical simulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-20 11:11:17","doi":"10.21203/rs.3.rs-4905258/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4c25177-b7f8-49cb-8dc3-0bd373e31601","owner":[],"postedDate":"September 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":37842106,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":37842107,"name":"Earth and environmental sciences/Ecology/Forestry"}],"tags":[],"updatedAt":"2024-10-07T19:38:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-20 11:11:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4905258","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4905258","identity":"rs-4905258","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}