Particulate matter (PM) is one of the most serious environmental problems, exacerbating respiratory and vascular illnesses. Plants have the ability to reduce non-point source PM pollution through retention on leaves and branches. Studies of the dynamic processes of PM retention by plants and the mechanisms influencing this process will help to improve the efficiency of urban greening for PM reduction. We examined dynamic processes of PM retention and the major factors influencing PM retention by six trees with different branch structure characteristics in wind tunnel experiments at three different wind speeds. The results showed that the changes of PM numbers retained by plant leaves over time were complex dynamic processes for which maximum values could exceed minimum values by over 10 times. The average value of PM measured in multiple periods and situations can be considered a reliable indicator of the ability of the plant to retain PM. The dynamic processes were similar for PM₁₀ and PM₂.₅. They could be clustered into three groups simulated by continually-rising, inverse U-shaped, and U-shaped polynomial functions, respectively. The processes were the synthetic effect of characteristics such as species, wind speed, period of exposure and their interactions. Continually-rising functions always explained PM retention in species with extremely complex branch structure. Inverse U-shaped processes explained PM retention in species with relatively simple branch structure and gentle wind. The U-shaped processes mainly explained PM retention at high wind speeds and in species with a relatively simple crown. These results indicate that using plants with complex crowns in urban greening and decreasing wind speed in plant communities increases the chance of continually-rising or inverse U-shaped relationships, which have a positive effect in reducing PM pollution.

Understanding the transformation of nanoparticles emitted from vehicles is essential for developing appropriate methods for treating fine scale particle dynamics in dispersion models. This article provides an overview of significant research work relevant to modelling the dispersion of pollutants, especially nanoparticles, in the wake of vehicles. Literature on vehicle wakes and nanoparticle dispersion is reviewed, taking into account field measurements, wind tunnel experiments and mathematical approaches. Field measurements and modelling studies highlighted the very short time scales associated with nanoparticle transformations in the first stages after the emission. These transformations strongly interact with the flow and turbulence fields immediately behind the vehicle, hence the need of characterising in detail the mixing processes in the vehicle wake. Very few studies have analysed this interaction and more research is needed to build a basis for model development. A possible approach is proposed and areas of further investigation identified.

A new vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel investigations was developed. The modeling concept is based on fluid dynamical similarity aspects and allows the small-scale modeling of various kinds of vegetation, e.g. field crops, shrubs, hedges, single trees and forest stands. The applicability of the modeling concept was validated in wind tunnel pollutant dispersion studies. Avenue trees in urban street canyons were modeled and their implications on traffic pollutant dispersion were investigated. The dispersion experiments proved the modeling concept to be practicable for wind tunnel studies and suggested to provide reliable concentration results. Unfavorable effects of trees on pollutant dispersion and natural ventilation in street canyons were revealed. Increased traffic pollutant concentrations were found in comparison to the tree-free reference case.

High concentration particulate matter 2.5 released from forest fires, in addition to direct burns and asphyxia, PM₂.₅ is one of the main pollutants which threaten the safety of forest fire fighter. Therefore, to assess spatial distribution of PM₂.₅, a simulation study was conducted. Fuel beds with different moisture contents and loads were constructed. 144 times burning experiments were carried out under different wind speeds by using wind tunnel device. PM₂.₅ particles at different spatial points were collected and calculated. The results show that, in the two of three variables interaction between wind speed, fuel load, and, except fuel moisture content, wind speed and fuel load are positively correlated with the PM₂.₅ concentrations. From PM₂.₅ concentration which collected at each point in the horizontal and vertical directions, the overall trend is that PM₂.₅ concentration increases along the horizontal downwind direction (C and D higer than A and B) and the vertical upward direction (A and C higer than B and D) Based on BP neural network, the spatial distribution model of PM₂.₅ concentration with single hidden layer was established. The prediction accuracy of modeling samples and validation samples is balanced when hidden layer node is 5. This study will help to make reference for PM₂.₅ occupational exposure standards, forest fire smoke management and forest fire management in China.

Global urban planning has promoted green infrastructure (GI) such as street trees, shrubs or other greenspace in order to mitigate air pollution. Although considerable attention has been paid to understanding particulate matter (PM) deposition on GI, there has been little focus on identifying which leaf traits might maximise airborne PM removal. This paper examines existing literature to synthesize the state of knowledge on leaf traits most relevant to PM removal. We systematically reviewed measurement studies that evaluated particulate matter accumulated on leaves on street trees, shrubs green roofs, and green walls, for a variety of leaf traits. Our final selection included 62 papers, most from field studies and a handful from wind tunnel studies. The following were variously promoted as useful traits: coniferous needle leaves; small, rough and textured broadleaves; lanceolate and ovate shapes; waxy coatings, and high-density trichomes. Consideration of these leaf traits, many of which are also associated with drought tolerance, may help to maximise PM capture. Although effective leaf traits were identified, there is no strong or consistent evidence to identify which is the most influential leaf trait in capturing PM. The diversity in sampling methods, wide comparison groups and lack of background PM concentration measures in many studies limited our ability to synthesize results. We found that several ancillary factors contribute to variations in the accumulation of PM on leaves, thus cannot recommend that selection of urban planting species be based primarily on leaf traits. Further research into the vegetation structural features and standardization of the method to measure PM on leaves is needed.

The city of London, UK, has seen in recent years an increase in the number of high-rise/multi-storey buildings (“skyscrapers”) with roof heights reaching 150 m and more, with the Shard being a prime example with a height of ∼310 m. This changing cityscape together with recent plans of local authorities of introducing Combined Heat and Power Plant (CHP) led to a detailed study in which CFD and wind tunnel studies were carried out to assess the effect of such high-rise buildings on the dispersion of air pollution in their vicinity. A new, open-source simulator, FLUIDITY, which incorporates the Large Eddy Simulation (LES) method, was implemented; the simulated results were subsequently validated against experimental measurements from the EnFlo wind tunnel. The novelty of the LES methodology within FLUIDITY is based on the combination of an adaptive, unstructured, mesh with an eddy-viscosity tensor (for the sub-grid scales) that is anisotropic. The simulated normalised mean concentrations results were compared to the corresponding wind tunnel measurements, showing for most detector locations good correlations, with differences ranging from 3% to 37%. The validation procedure was followed by the simulation of two further hypothetical scenarios, in which the heights of buildings surrounding the source building were increased. The results showed clearly how the high-rise buildings affected the surrounding air flows and dispersion patterns, with the generation of “dead-zones” and high-concentration “hotspots” in areas where these did not previously exist. The work clearly showed that complex CFD modelling can provide useful information to urban planners when changes to cityscapes are considered, so that design options can be tested against environmental quality criteria.

Glyphosate is one of the most used herbicides in agricultural lands worldwide. Wind-eroded sediment and dust, as an environmental transport pathway of glyphosate and of its main metabolite aminomethylphosphonic acid (AMPA), can result in environmental- and human exposure far beyond the agricultural areas where it has been applied. Therefore, special attention is required to the airborne transport of glyphosate and AMPA. In this study, we investigated the behavior of glyphosate and AMPA in wind-eroded sediment by measuring their content in different size fractions (median diameters between 715 and 8 μm) of a loess soil, during a period of 28 days after glyphosate application. Granulometrical extraction was done using a wind tunnel and a Soil Fine Particle Extractor. Extractions were conducted on days 0, 3, 7, 14, 21 and 28 after glyphosate application. Results indicated that glyphosate and AMPA contents were significantly higher in the finest particle fractions (median diameters between 8 and 18 μm), and lowered significantly with the increase in particle size. However, their content remained constant when aggregates were present in the sample. Glyphosate and AMPA contents correlated positively with clay, organic matter, and silt content. The dissipation of glyphosate over time was very low, which was most probably due to the low soil moisture content of the sediment. Consequently, the formation of AMPA was also very low. The low dissipation of glyphosate in our study indicates that the risk of glyphosate transport in dry sediment to off-target areas by wind can be very high. The highest glyphosate and AMPA contents were found in the smallest soil fractions (PM10 and less), which are easily inhaled and, therefore, contribute to human exposure.

Trees can improve air quality by capturing particles in their foliage. We determined the particle capture efficiencies of coniferous Pinus sylvestris and three broadleaved species: Betula pendula, Betula pubescens and Tilia vulgaris in a wind tunnel using NaCl particles. The importance of leaf surface structure, physiology and moderate soil drought on the particle capture efficiencies of the trees were determined. The results confirm earlier findings of more efficient particle capture by conifers compared to broadleaved plants. The particle capture efficiency of P. sylvestris (0.21%) was significantly higher than those of B. pubescens, T. vulgaris and B. pendula (0.083%, 0.047%, 0.043%, respectively). The small leaf size of P. sylvestris was the major characteristic that increased particle capture. Among the broadleaved species, low leaf wettability, low stomatal density and leaf hairiness increased particle capture. Moderate soil drought tended to increase particle capture efficiency of P. sylvestris.

Air quality management in urban areas requires the use of advanced modeling tools, able to predict and evaluate the pollution level under different traffic and meteorological conditions. In the present paper, the Artificial Compressibility version of the Characteristic Based Split algorithm (AC–CBS) was used to assess the performance of the Spalart–Allmaras based Detached Eddy Simulation (SA–DES) model, for the calculation of incompressible turbulent flow in different urban street canyon configurations. To our knowledge, the DES version of the SA turbulence model was applied in this work for the first time for the simulation of turbulent flow in a street canyon. The proposed DES model was able to accurately reproduce the turbulent characteristics of the flow compared with results from real street canyon experiments, wind tunnel experiments, and also to that obtained with RANS simulations. These results are very similar to the ones obtained from Large Eddy Simulation (LES) of street canyons flow reported in some recent publications, but with the potential characteristic of reduced computational costs. The DES approach is very promising for the simulation of transient turbulent flows in urban areas when complex three–dimensional domains are considered. The performance of the DES model evaluated for the mean dimensionless streamwise velocity profiles was comparable to that of Reynolds–Averaged Navier–Stokes RANS approach if referred to Hit Rate (HR) validation metric, and even better if referred to Factor of two observation (FAC2) validation metric. An accurate reproduction of the turbulent flow is crucial for urban pollutant dispersion simulations, since the distribution of the pollutant concentrations could differ by order of magnitude in the different points of the street canyon. DES approach results were able to accurately predict the unsteadiness characteristic of the flow, and to reproduce some minor vortex structures, which were not observed in the RANS cases, that will lead to a more accurate reproduction of the pollutant concentrations.

The direct effect of atmospheric turbulence on plume rise in the current research work is studied through examining the turbulence intensity parameter. A hybrid unsteady Reynolds averaged Navier Stokes (RANS) and large eddy simulation (LES) numerical approach is applied with a new mixed scale sub-grid parameterization technique in the commercial ANSYS Fluent software in order to simulate the buoyant plume behavior in a turbulent crossflow. The accuracy of the simulation method is crosschecked against the wind tunnel data available in the literature. The numerical simulation results in various operating conditions are used to derive a new plume rise formula in which the direct effect of atmospheric turbulence intensity at stack height (IAir) is explicitly introduced in the plume rise formula. Furthermore, the buoyancy parameter of the flue gas is determined at some distances upstream of the stack top surface to include the whole effects of source buoyancy on the plume rise. The value of IAir at stack height is obtained by measuring the standard deviation of wind velocity at stack height. The sensitivity analysis showed that by increasing the atmospheric turbulence intensity, the final plume rise decreases because of the updraft and downdraft motions of turbulence and it has been found that there is a linear dependency between the plume rise and (IAir)−1.22. The quantile-quantile plots show that the new model can predict the simulated plume rise with a deviation factor of 1.0025 whereas the conventional models overestimate the final plume rise at least by a factor of 2.2.