Review on urban tree modelling in CFD simulations: Aerodynamic, deposition and thermal effects

Buccolieri, Riccardo; Santiago, José Luis; Rivas, Esther; Sánchez, Beatríz

doi:10.1016/j.ufug.2018.03.003

Cited by 155 publications

(81 citation statements)

References 74 publications

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“…Thus, the pollutant accumulated within the street canyons is closer to the pollutant source upwind with poor pollution transport downwind. The ventilation gets worse in the presence of vegetation as the concentration distribution suggests that the aerodynamic effect seemed to prevail over the filtering capacity [18][19][20][21][22]. To further show the effect of vegetation on pollutant dispersion, as an example Figure 16 shows that, for Case A, the area where the PM10 concentration is below 10 µg/m 3 almost accounts for 64% and the maximum PM10 concentration in the residential district is about 50 µg/m 3 .…”

Section: The Impact Of Green Space Layout On Pm10 Concentrationmentioning

confidence: 99%

“…The deposition of particles on vegetation surfaces can be influenced by various factors, such as the diameter and shape of the particles, the planting configuration and meteorological parameters. Although the deposition on vegetation helps to remove particles from the air [15][16][17][18], the aerodynamic effects may reduce the air exchange compared with a no-green scenario, reducing mixing, dilution and ventilation [18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Green Space Layouts on Microclimate and Air Quality in Residential Districts of Nanjing, China

Rui

Buccolieri

Gao

et al. 2018

Forests

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This study numerically investigates the influence of different vegetation types and layouts on microclimate and air quality in residential districts based on the morphology and green layout of Nanjing, China. Simulations were performed using Computational Fluid Dynamics and the microclimate model ENVI-met. Four green indices, i.e., the green cover ratio, the grass and shrub cover ratio, the ecological landscaping plot ratio and the landscaping isolation index, were combined to evaluate thermal and wind fields, as well as air quality in district models. Results show that under the same green cover ratio (i.e., the same quantity of all types of vegetation), the reduction of grass and shrub cover ratio (i.e., the quantity of grass and shrubs), replaced by trees, has an impact, even though small, on thermal comfort, wind speed and air pollution, and increases the leisure space for occupants. When trees are present, a low ecological landscaping plot ratio (which expresses the weight of carbon dioxide absorption and is larger in the presence of trees) is preferable due to a lower blocking effect on wind and pollutant dispersion. In conjunction with a low landscaping plot ratio, a high landscaping isolation index (which means a distributed structure of vegetation) enhances the capability of local cooling and the general thermal comfort, decreasing the average temperature up to about 0.5 • C and the average predicted mean vote (PMV) up to about 20% compared with the non-green scenario. This paper shows that the relationship vegetation-microclimate-air quality should be analyzed taking into account not only the total area covered by vegetation but also its layout and degree of aggregation.

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Section: The Impact Of Green Space Layout On Pm10 Concentrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Impact of Green Space Layouts on Microclimate and Air Quality in Residential Districts of Nanjing, China

Rui

Buccolieri

Gao

et al. 2018

Forests

Self Cite

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“…During dry seasons such as autumn, increasing interaction between greenspace and other elements in urban areas by higher ED and LPI would lead to faster near-ground wind speed and increases in air humidity, and the strong wind may lead to higher PM concentration under higher humidity [54,55]. In addition, the aerodynamic effects of greenspace are stronger than the positive effects of deposition [28,29], and more trees in a street canyon may lead to a reduction of ventilation and an average increase of air pollution [28], and it was reported that high-level vegetation canopies (trees) led to a deterioration in air quality, while low-level green infrastructure (hedges) improved air-quality conditions [27]. The relationship between spatial patterns and PM concentration varied in different seasons and scales, and the landscape metrics of greenspace influenced PM concentration in both positive and negative manners, thus, the usefulness of greenspace in reducing PM concentration hinges on the balance between these pros and cons.…”

Section: Scale-dependent Effects Of Greenspace Pattern On Pm Pollutionmentioning

confidence: 99%

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Lei

Duan

et al. 2018

Atmosphere

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This case study was conducted to quantify the effects of urban greenspace patterns on particle matter (PM) concentration in Zhengzhou, China by using redundancy and variation partitioning analysis. Nine air-quality monitoring stations (AQMS) were selected as the central points. Six distances of 1 km, 2 km, 3 km, 4 km, 5 km, and 6 km were selected as the side lengths of the squares with each AQMS serving as the central point, respectively. We found:(1) the fine size of PM (PM 2.5 ) and coarse size of PM (PM 10 ) among four seasons showed significant differences; during winter, the concentration of PM 2.5 and PM 10 were both highest, and PM 2.5 and PM 10 concentration in summer were lowest. (2) To effectively reduce the PM 2.5 pollution, the percentage of greenspace, the differences in areas among greenspace patches, and the edge complexity of greenspace patches should be increased at distances of 2 km and 3 km. To effectively reduce PM 10 , the percentage of greenspace at a distance of 4 km, the edge density at distances of 2 km and 4 km, and the average area of greenspace patches at a distance of 1 km should be increased. (3) Greenspace pattern significantly affected PM 2.5 at a distance of 3 km, and PM 10 at a distance of 4 km. From shorter distance to longer distance, the proportion of variance explained by greenspace showed a decline-increase-decline-increase trend for PM 2.5 , and a decline-increase-decline trend for PM 10 . At shorter distances, the composition of greenspace was more effective in reducing the PM pollution, and the configuration of greenspace played a more important role at longer distances. The results should lead to specific guidelines for more cost-effective and environmentally sound greenspace planning.

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“…It is evident that the pursuit of sustainable urban development depends on an accurate understanding of urban ecosystem services, which requires baseline data on forest structure and functions [28]. Tree density and biomass either implicitly affect the ecosystem services described above, e.g., pollutant dispersion and deposition [21,22,29,30], transpirational cooling [19,29], and precipitation interception [20,23,31], or directly determines the quantity of the services such as carbon stored and sequestered and timber and biofuels garnered [17,18]. Biological quantities of vegetation (e.g., leaf areas and biomass), in addition to the area coverage and distribution, have been factored into sustainability indicators to evaluate the functions of urban vegetation in supporting the resilience of human-environment systems [32,33].…”

Section: Introductionmentioning

confidence: 99%

Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

2019

Sustainability

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Urban trees provide various important ecological services, the quantification of which is vital to sustainable urban development and requires accurate estimation of tree biomass. A limited number of allometric biomass equations, however, have been developed for urban species due to the prohibitive cost. Remote sensing has provided cost-effective means for estimating urban forest biomass, although the propagation of error in the estimation process is not well understood. This study aimed to offer a baseline assessment of the feasibility of estimating urban tree biomass with remote sensing-based general equations applicable to broad taxonomic groups by conducting a large urban tree inventory on a university campus. The biomasses of 191 trees of seven species from the inventory, separated into two categories (i.e., evergreen and deciduous), were calculated exclusively with urban-based species-specific allometric equations. WorldView-2 satellite imagery data were acquired to retrieve normalized difference vegetation index (NDVI) values at the location, crown, and stand levels. The results indicated that biomass correlated with NDVI in varying forms and degrees. The general equations at the crown level yielded the most accurate biomass estimates, while the location-level estimates were the least accurate. Crown-level spectral responses provided adequate information for delivering spatially explicit biomass estimation. could be substantial [50][51][52], ranging from −97% to 205% depending on the individual species and the sizes of the trees [43]. Biomass estimates could even vary from 27% less to 29% more when applying the allometric equation developed for an individual urban species in California to the same species in Colorado because of considerable differences in site conditions [43].Considering the time and monetary cost of developing site-and species-specific allometric equations, it has been suggested to use general equations that are applicable to all species in a broad taxonomic grouping instead [43,53,54]. Such equations have been developed for 35 natural forest-grown genera on a national scale [39,40]. However, studies focused on developing allometric equations for general urban tree groups are scant [49], because urban-based equations over the entire range of site conditions are not available for compilation and synthesis [55].Another approach to overcome the prohibitive cost associated with the development of allometric equations is to utilize remote sensing and geospatial techniques [49,[56][57][58][59][60]. Remote sensing obtains information about the Earth's environment from a distance without the need for extensive field surveys over large areas. It has been used in several different ways as a non-destructive and cost-effective method for biomass estimation with varying degrees of success.Generated with Light Detection and Ranging (LiDAR) technology, point cloud data have been regularly used to measure urban tree biomass directly [58,[60][61][62] or extract basic silvicultural variables such as tree he...

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Review on urban tree modelling in CFD simulations: Aerodynamic, deposition and thermal effects

Cited by 155 publications

References 74 publications

The Impact of Green Space Layouts on Microclimate and Air Quality in Residential Districts of Nanjing, China

The Impact of Green Space Layouts on Microclimate and Air Quality in Residential Districts of Nanjing, China

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

Developing General Equations for Urban Tree Biomass Estimation with High-Resolution Satellite Imagery

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