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The identification of parameters that can quantitatively describe the different characteristics of urban morphology is fundamental to studying urban ventilation and microclimate at the local level and developing parameterizations of the dynamic effect of an urban area in mesoscale models. This paper proposes a methodology to calculate four morphological parameters, namely mean height, aspect ratio, sky view factor, and plan area ratio, of five cities located in southern (Bari and Lecce), central (Naples and Rome), and northern (Milan) Italy. The calculation is performed using the Geographical Information System (GIS), starting from morphological and land use data collected and analyzed in shapefiles. The proposed methodology, which can be replicated in other cities, also presents in detail the procedure followed to properly build input data to calculate the sky view factor using the UMEP GIS tool. The results show a gradual increase in the plan area index, λp, and mean building height, H¯, moving from the south to the north of Italy. Maximum values of λp and H¯ are obtained in the regions of Milan, Rome, and Naples, where the highest spatially-averaged values are also found, i.e., λp = 0.22, H¯ = 10.9 m in Milan; λp = 0.19, H¯ = 12.7 m in Rome; λp = 0.20, H¯ = 12 m in Naples. Furthermore, for all the cities investigated, areas characterized by the Corine Land Cover class as “continuous urban fabric” are those with medium sky view factor SVF values (around 0.6–0.7) and λp values (around 0.3) typical of intermediate/compact cities. The methodology employed here for calculating morphological parameters using GIS proves to be replicable in different urban contexts. This opens to a better classification of cities in local climate zones (LCZ), as shown for the Lecce region, useful for urban heat island (UHI) studies and to the development of parameterizations of the urban effects in global and regional climate models.

Through a unified mathematical framework, the stochastic behavior of three celebrated low-order lumped models, previously proposed for paleoclimate simulations, is considered. Due to the coherence resonance mechanism, the feedbacks between noise and the dynamical system reproduce the hallmark of the Pleistocene climate, i.e. the 100 ky pulsation, in a range of the model parameters that is unexpectedly wide and far from the original modeling setting. In this way, the issue of arbitrary coefficient tuning of lumped approaches in paleoclimatology can be partially bypassed. A stability analysis of the considered dynamical systems allowed the parameter space to be exploited, in order to separate the deterministic-dominated region from the stochastic-dominated region. Noise intensity is varied and the closeness in the parameter space to Hopf bifurcations and/or bistable conditions is investigated in order to understand what conditions make the models prone to coherence resonance with a 100-ky pulsation, with or without the forcing induced by varying astronomical parameters.

Dioxins, are persistent organic pollutants with endocrine disrupting properties and are classified as human carcinogens. To better characterise historical atmospheric dioxin exposure in epidemiological studies, we performed a comprehensive inventory of dioxin-emitting sources between 1990 and 2008, in France, at a fine spatial resolution, according to the methodology of the United Nations Environment Program (UNEP) Toolkit. Overall, we identified 2620 distinct dioxin-emitting sources over the French territory. The majority of the sources were geolocated either at the stack (43%) or at the building (27%). The final database contains the technical characteristics and activity rates for each source over the study period. These data served to estimate total annual dioxin emissions (g-TEQ/year). We compared our estimates with both measurements and emissions inventories (at departmental and national level). The discrepancies in the comparisons between the Toolkit estimates, the dioxin measurements available, and inventories remained within the uncertainty range of the UNEP Toolkit estimates. The differences observed were due to a general lack of data and to the large number of small incinerators with large dioxin emissions inventoried. Due to better access to relevant data and a decrease in emissions, the UNEP Toolkit estimates get closer to measurements and estimates of others inventories for more recent years. We created the first database containing the annual atmospheric dioxin emissions for a large number of emission sources at the facility scale for an entire country. This database was used to assess exposure to dioxins in epidemiological studies.

We review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models.

Several European urban areas are characterised by low air quality due to high local emission per unit surface. A further key feature can be related to the pollutant load due to adverse local meteo-climatic conditions. This study aims to compare the two urban agglomerations of Torino and Lyon – located on opposite sides of the Alps and characterised by similar size and population – to enlighten the role of meteorology on local pollutant dispersion. The assessment of air quality has been developed by monitoring network data, emissions analysis and the SIRANE urban dispersion model. Although the two agglomerations have similar NOX and PM10 emissions, the simulation results show higher ground level concentrations in Torino. To quantify the effect of meteorology on this excess of concentrations, we run simulations in Torino imposing the meteorological conditions of Lyon and vice versa. This implies an overall reduction of ground level concentrations in the city centre of Torino between 20% and 40% (analogously, Lyon concentrations increase by a similar amount). These results show the peculiar difficulties faced by Po valley's cities in maintaining pollution levels below regulatory thresholds and highlight the need of systemic policies and site-specific mitigation to reduce air pollution health risks.

The concentration of a passive scalar dispersed in a turbulent flow exhibits a complex stochastic dynamics. In this paper, we present a minimalist stochastic model that resembles the concentration statistics of a passive scalar emitted from a localized source in a neutral boundary layer. The model provides closed forms for the crossing rates and times — the mean frequency of exceeding a certain concentration level and the mean time above it. Three concentration statistics are needed as model inputs: the mean, the standard deviation, and the integral scale. By giving analytical relationships also for these statistics, we provide a completely closed methodology that may serve as a rapid and practical tool to estimate the dynamics of a pollutant dispersed in the atmosphere. Results are validated against wind-tunnel measurements.

The large-eddy simulation (LES) model uDALES is used to evaluate the predictive skill of the operational air quality model SIRANE. The use of LES in this study presents a novel approach to air quality model evaluation, avoiding sources of uncertainty and providing numerical control that permits systematic analysis of targeted parametrisations and assumptions.A case study is conducted over South Kensington, London with the morphology, emissions, meteorological conditions and boundary conditions carefully matched in both models. The dispersion of both inert (NOx) and reactive (NO, NO2 and O3) pollutants under neutral, steady-state conditions is simulated for a south-westerly and westerly wind direction. A quantitative comparison between the two models is performed using statistical indices (the fractional bias, FB, the normalised mean squared error, NMSE, and the fraction in a factor of 2, FAC2).SIRANE is shown to successfully capture the dominant trends with respect to canyon-averaged concentrations of inert NOx (FB = −0.08, NMSE = 0.08 and FAC2 = 1.0). The prediction of along-canyon velocities is shown to exhibit sources of systematic error dependant on the angle of incidence of the mean wind (FB = −0.18). The assumption of photostationarity within SIRANE (deviations from equilibrium of up to 170% exist close to busy roads) is also identified as a significant source of systematic bias resulting in over- and underpredictions of NO2 (FB = −0.18) and O3 (FB = 0.14) respectively. The validity of the assumed uniform in-canyon concentration is assessed by analysing the pedestrian, leeward and windward concentrations resolved in uDALES. The use of canyon-averaged concentrations to predict pedestrian level exposure is shown to result in significant underestimations. Linear regression is used to effectively capture the relationship between pedestrian- and canyon-averaged concentrations in uDALES. Correction factors are derived (m≈1.62 and R2=0.92 for inert NOx) that are capable of significantly improving SIRANE's ability to assess pedestrian level exposure for the conditions investigated in this study. The prevalence of intersections and advective nature of the shear layer are highlighted as important differences between modelling real heterogeneous urban morphology and idealised infinite canyons. Keywords: Urban air quality, Model evaluation, Large-eddy simulation, Street canyon modelling, Traffic emissions, Pollutant dispersion

[...]this topic is highly interdisciplinary and requires the cooperation of science, technology, and policies to reach the final aim. [...]a dramatic difference in the concentrations of FPs was observed [2] between vehicular (8.0 × 104 #/cm3) and pedestrian streets (average 3.3 × 104 #/cm3). The streets are remarkably close to each other, with similar aspect ratio height of buildings/street width (H/W) and the same orientation. [...]it must be concluded that local vehicular traffic is the main source of the high FP concentration observed in the monitored area [2]. [...]through a hot spot analysis, statistically significant spatial clusters of high-concentration and low-concentration values were identified.

International audience; We analyze the reliability of the Lagrangian stochastic micromixing 8 method in predicting higher-order statistics of the passive scalar concentration in-9 duced by an elevated source (of varying diameter) placed in a turbulent boundary 10 layer. To that purpose we analyze two different modelling approaches by testing 11 their results against the wind-tunnel measurements discussed in Part I (Nironi 12 et al., Boundary-Layer Meteorology, 2015, Vol.156, 415-446). The first is a prob-13 ability density function (PDF) micromixing model that simulates the effects of 14 the molecular diffusivity on the concentration fluctuations by taking into account 15 the background particles. The second is a new model, named VPΓ , conceived in 16 order to minimize the computational costs. This is based on the volumetric par-17 ticle approach providing estimates of the first two concentration moments with 18 no need for the simulation of the background particles. In this second approach, 19 higher-order moments are computed based on the estimates of these two moments 20 and under the assumption that the concentration PDF is a Gamma distribution. 21 The comparisons concern the spatial distribution of the first four moments of the 22 concentration and the evolution of the PDF along the plume centreline. The nov-23 elty of this work is twofold: i) we perform a systematic comparison of the results 24 of micro-mixing Lagrangian models against experiments providing profiles of the 25 first four moments of the concentration within an inhomogeneous and anisotropic 26 turbulent flow, and ii) we show the reliability of the VPΓ model as an operational 27 tool for the prediction of the PDF of the concentration. 28

We investigate the reliability of a meandering plume model in reproducing the passive scalar concentration statistics due to a continuous release in a turbulent boundary layer. More specifically, we aim to verify the physical consistency of the parametrizations adopted in the model through a systematic comparison with experimental data. In order to perform this verification, we take advantage of the velocity and concentration measurements presented in part I of the present study (Nironi et al., Boundary-Layer Meteorol, 2015) particularly concerning estimates of the Eulerian integral length scales and the higher order moments of the concentration probability density function. The study is completed by a sensitivity analysis in order to estimate the effects of the variations of the key parameter to the model results. In the light of these results, we discuss the benefits and shortcomings of this modelling approach and its suitability for operational purposes.

Developing effective strategies for reducing the atmospheric pollutant concentrations below regulatory threshold levels requires identifying the main origins/sources of air pollution. This can be achieved by implementing so called source apportionment methods in atmospheric dispersion models. This study presents the results of a source apportionment module implemented in the SIRANE urban air-quality model. This module uses the tagged species approach and includes two methods, named SA-NO and SA-NOX, in order to evaluate the sources’ contributions to the NO 2 concentrations in air. We also present results of a data assimilation method, named SALS, that uses the source apportionment estimates to improve the accuracy of the SIRANE model results. The source apportionment module and the assimilation method have been tested on a real case study (the urban agglomeration of Lyon, France, for the year 2008) focusing on the NO 2 emissions and concentrations. Results of the source apportionment with the SA-NO and SA-NOX models are similar. Both models show that traffic is the main cause of NO 2 air pollution in the studied area. Results of the SALS data assimilation method highlights its ability in improving the predictions of an urban atmospheric models.

We present a validation study of an updated version of the SIRANE model, whose results have been systematically compared to concentrations of nitrogen dioxide collected over the whole urban agglomeration of Lyon. We model atmospheric dispersion of nitrogen oxides emitted by road traffic, industries and domestic heating. The meteorological wind field is computed by a pre-processor using data collected at a ground level monitoring station. Model results are compared with hourly concentrations measured at 15 monitoring stations over the whole year (2008). Further 75 passive diffusion samplers were used during 3 periods of 2 weeks to get a detailed spatial distribution over the west part of the city. An analysis of the model results depending on the variability of the meteorological input allows us to identify the causes for peculiar bad performances of the model and to identify possible improvements of the parameterisations implemented in it.

We present an inverse atmospheric model to estimate the mass flow rate of an impulsive source of pollutant, whose position is known, from concentration signals registered at receptors placed downwind of the source. The originality of this study is twofold. Firstly, the inversion is performed using high-frequency fluctuating, i.e. turbulent, concentration signals. Secondly, the inverse algorithm is applied to a dispersion process within a dense urban canopy, at the district scale, and a street network model, SIRANERISK, is adopted. The model, which is tested against wind tunnel experiments, simulates the dispersion of short-duration releases of pollutant in different typologies of idealised urban geometries. Results allow us to discuss the reliability of the inverse model as an operational tool for crisis management and the risk assessments related to the accidental release of toxic and flammable substances.

Background: Air pollution is a major global environmental risk factor. Since people spend most of their time indoors, the sole measure of outdoor concentrations is not sufficient to assess total exposure to air pollution. Therefore, the arising interest by the international community to indoor-outdoor relationships has led to the development of various techniques for the study of emission and exchange parameters among ambient and non-ambient pollutants. However, a standardised method is still lacking due to the complex release and dispersion of pollutants and the site conditions among studies. Methods: This review attempts to fill this gap to some extent by focusing on the analysis of the variety of site-specific approaches for the assessment of particulate matter in work and life environments. Results: First, the main analogies and differences between indoor and outdoor particles emerging from several studies are briefly described. Commonly-used indicators, sampling methods, and other approaches are compared. Second, recommendations for further studies based on recent results in order to improve the assessment and management of those issues are provided. Conclusions: This review is a step towards a comprehensive understanding of indoor and outdoor exposures which may stimulate the development of innovative tools for further epidemiological and multidisciplinary research.

SIRANERISK is an operational model for the simulation of the dispersion of unsteady atmospheric releases of pollutant within and above an urban area. SIRANERISK is built on the same principles as the SIRANE model, and couples a street network model for the pollutant transfers within the urban canopy with a Gaussian puff model for the transfers above it. The performance of the model are here analysed by a detailed comparisons with wind-tunnel experiments. These experiments concern the dispersion of steady and unsteady pollutant releases within and above obstacle arrays with varying geometrical configurations, representing different topologies of idealised urban districts. The overall good agreement between numerical and experimental data demonstrates the reliability of SIRANERISK as an operational tool for the assessment of risk analysis and for the management of crises due to the accidental release of harmful airborne pollutants within a built environment.

An analytical model has been developed for the flow along a street canyon (of height H and width W), generated by an external wind blowing at any angle relative to the axis of the street. Initially, we consider the special case of a wind blowing parallel to the street. The interior of the street is decomposed into three regions, and the flow within each region is assumed to depend only on the external wind and the distance to the closest solid boundary. This decomposition leads to two different flow regimes: one for narrow streets (H/W > 1/2) and one for wide streets (H/W < 1/2). The theoretical model agrees well with results obtained from numerical simulations using a Reynolds-Averaged Navier–Stokes model. We then generalize the model to the case of arbitrary wind direction. Numerical solutions show that the streamlines of the mean flow in the street have a spiral form, and for most angles of incidence, the mass flux along the street scales on the component of the external wind resolved parallel to the street. We use this result to generalize the model derived for wind blowing parallel to the street, and the results from this model agree well with the numerical simulations. The model that has been developed can be evaluated rapidly using only very modest computing power, so it is suitable for use as an operational tool.

This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.

Breathability in dense building arrays with packing densities similar to those of typical European cities is investigated using laboratory measurements and numerical simulations. We focus on arrays made up by regularly spaced square buildings forming a network of streets with right-angle intersections. It is shown that breathability can be evaluated using building ventilation concepts (mean flow rate and age of air) and from vertical mean and turbulent fluxes quantifiable through a bulk exchange velocity. Mean age of air reveals that varying wind angles result in different ventilation, which we explain through mean flow streamlines and exchange velocity. For low wind angles (wind direction almost parallel to the axes of half of the streets of the network), vertical transfer and mean transversal transfers are at minimum and removal of pollutants is associated with mean longitudinal fluxes. Larger wind angles result in better ventilation due to an increase of transversal fluxes and vertical exchange. The latter, for which a formulation is derived, shows a non-negligible contribution of the mean flow which increases with increasing wind angle. Ventilation conditions can be further altered by small differences in the array geometry. These observations are useful for the development of simple urban dispersion models.

The prediction of the probability density function (PDF) of a pollutant concentration within atmospheric flows is of primary importance in estimating the hazard related to accidental releases of toxic or flammable substances and their effects on human health. This need motivates studies devoted to the characterization of concentration statistics of pollutants dispersion in the lower atmosphere, and their dependence on the parameters controlling their emissions. As is known from previous experimental results, concentration fluctuations are significantly influenced by the diameter of the source and its elevation. In this study, we aim to further investigate the dependence of the dispersion process on the source configuration, including source size, elevation and emission velocity. To that end we study experimentally the influence of these parameters on the statistics of the concentration of a passive scalar, measured at several distances downwind of the source. We analyze the spatial distribution of the first four moments of the concentration PDFs, with a focus on the variance, its dissipation and production and its spectral density. The information provided by the dataset, completed by estimates of the intermittency factors, allow us to discuss the role of the main mechanisms controlling the scalar dispersion and their link to the form of the PDF. The latter is shown to be very well approximated by a Gamma distribution, irrespective of the emission conditions and the distance from the source. Concentration measurements are complemented by a detailed description of the velocity statistics, including direct estimates of the Eulerian integral length scales from two-point correlations, a measurement that has been rarely presented to date.

This study discusses the reliability of the street network approach for pollutant dispersion modelling in urban areas. This is essentially based on a box model, with parametric relations that explicitly model the main phenomena that contribute to the street canyon ventilation: the mass exchanges between the street and the atmosphere, the pollutant advection along the street axes and the pollutant transfer at street intersections. In the first part of the paper the focus is on the development of a model for the bulk transfer street/atmosphere, which represents the main ventilation mechanisms for wind direction that are almost perpendicular to the axis of the street. We then discuss the role of the advective transfer along the street axis on its ventilation, depending on the length of the street and the direction of the external wind. Finally we evaluate the performances of a box model integrating parametric exchange laws for these transfer phenomena. To that purpose we compare the prediction of the model to wind tunnel experiments of pollutant dispersion within a street canyon placed in an idealised urban district.

We analyse the performance of the model SIRANE by comparing its outputs to field data measured within an urban district. SIRANE is the first urban dispersion model based on the concept of street network, and contains specific parametrical law to explicitly simulate the main transfer mechanisms within the urban canopy. The model validation is performed by means of field data collected during a 15 days measurement campaign in an urban district in Lyon, France. The campaign provided information on traffic fluxes and cars emissions, meteorological conditions, background pollution levels and pollutant concentration in different location within the district. This data set, together with complementary modelling tools needed to estimate the spatial distribution of traffic fluxes, allowed us to estimate the input data required by the model. The data set provide also the information essential to evaluate the accuracy of the model outputs. Comparison between model predictions and field measurements was performed in two ways. By evaluate the reliability of the model in simulating the spatial distribution of the pollutant and of their time variability. The study includes a sensitivity analysis to identify the key input parameters influencing the performance of the model, namely the emissions rates and the wind velocity. The analysis focuses only on the influence of varying input parameters in the modelling chain in the model predictions and complements the analyses provided by wind tunnel studies focussing on the parameterisation implemented in the model. The study also elucidates the critical role of background concentrations that represent a significant contribution to local pollution levels. The overall model performance, measured using the Chang and Hanna (2004) criteria can be considered as ‘good’ except for NO and some of BTX species. The results suggest that improvements of the performances on NO require testing new photochemical models, whereas the improvement on BTX could be achieved by correcting their vehicular emissions factors.

In order to control and manage urban air quality, public authorities require an integrated approach that incorporates direct measurements and modelling of mean pollutant concentrations. These have to be performed by means of operational modelling tools, that simulate the transport of pollutants within and above the urban canopy over a large number of streets. The operational models must be able to assess rapidly a large variety of situations and with limited computing resources. SIRANE is an operational urban dispersion model based on a simplified description of the urban geometry that adopts parametric relations for the pollutant transfer phenomena within and out of the urban canopy. The streets in a city district are modelled as a network of connected street segments. The flow within each street is driven by the component of the external wind parallel to the street, and the pollutant is assumed to be uniformly mixed within the street. The model contains three main mechanisms for transport in and out of a street: advection along the street axis, diffusion across the interface between the street and the overlying air flow and exchanges with other streets at street intersections. The dispersion of pollutants advected or diffused out of the streets is taken into account using a Gaussian plume model, with the standard deviations σy and σz parameterised by the similarity theory. The input data for the final model are the urban geometry, the meteorological parameters, the background concentration of pollutants advected into the model domain by the wind and the emissions within each street in the network.

The turbulent exchange of momentum between a two-dimensional cavity and the overlying boundary layer has been studied experimentally, using hot-wire anemometry and particle image velocimetry (PIV). Conditions within the boundary layer were varied by changing the width of the canyons upstream of the test canyon, whilst maintaining the square geometry of the test canyon. The results show that turbulent transfer is due to the coupling between the instabilities generated in the shear layer above the canyons and the turbulent structures in the oncoming boundary layer. As a result, there is no single, unique velocity scale that correctly characterizes all the processes involved in the turbulent exchange of momentum across the boundary layer. Similarly, there is no single velocity scale that can characterize the different properties of the turbulent flow within the canyon, which depends strongly on the way in which turbulence from the outer flow is entrained into the cavity and carried round by the mean flow. The results from this study will be useful in developing simple parametrizations for momentum exchange in the urban canopy, in situations where the street geometry consists principally of relatively long, uniform streets arranged in grid-like patterns; they are unlikely to be applicable to sparse geometries composed of isolated three-dimensional obstacles.

The influence of surface roughness on the dispersion of a passive scalar in a rough wall turbulent boundary layer has been studied using wind-tunnel experiments. The surface roughness was varied using different sizes of roughness elements, and different spacings between the elements. Vertical profiles of average concentration were measured at different distances downwind of the source, and the vertical spread of the plume was computed by fitting a double Gaussian profile to the data. An estimate of the integral length scale is derived from the turbulence characteristics of the boundary layer and is then used to scale the measured values of plume spread. This scaling reduces the variability in the data, confirming the validity of the model for the Lagrangian integral time scale, but does not remove it entirely. The scaled plume spreading shows significant differences from predictions of theoretical models both in the near and in the far field. In the region immediately downwind of the source this is due to the influence of the wake of the injector for which we have developed a simple model. In the far field we explain that the differences are mainly due to the absence of large-scale motions. Finally, further downwind of the source the scaled values of plume spread fall into two distinct groups. It is suggested that the difference between the two groups may be related to the lack of dynamical similarity between the boundary-layer flows for varying surface roughness or to biased estimates of the plume spread.

Street intersections play an important role in determining pollutant concentrations in the urban canopy – vehicle emissions often increase in the vicinity of road intersections, and the complex flow patterns that occur within the intersection determine the pollutant fluxes into adjoining streets and into the atmosphere. Operational models for urban air quality therefore need to take account of the particular characteristics of street intersections. We have performed an experimental and numerical investigation of flow and dispersion mechanisms within an urban intersection, and on the basis of our observations and results, we have developed a new operational model for pollutant exchanges in the intersection, which takes account of the non-uniformity of the pollutant fluxes entering and leaving the intersection. The intersection is created by two streets of square cross-section, crossing orthogonally; concentrations were measured by releasing a neutrally buoyant tracer gas from a line source located in one of the streets. As a general result, the numerical simulations agree well with the measurements made in the wind tunnel experiments, except for the case of ground-level concentrations, where the computed concentrations far from the axis of the line source are significantly lower than the measured values. In the first part of the study we investigate the influence of an intersection on the velocity and concentration fields in the adjoining streets; we show that the immediate influence of the intersection extends within the adjoining streets, to a distance of the order of the characteristic size of the streets. A large recirculating vortex is formed at the entrance to the cross-wind streets, and this determines the exchange of pollutants between the streets and the intersection. For some wind directions the average velocity in the street segment between intersections is the same as that which occurs in an infinitely long street with the same wind, but for other angles the average velocity in the finite-length street is significantly lower. The average concentration along a finite-length street is significantly different from that observed in an infinitely long street. In the second part of the study we investigate how the pollutant fluxes in the incoming streets are redistributed amongst the outgoing streets. An analysis of the mean streamlines shows that the flows remain relatively planar, with little variation over the vertical, and we have exploited this result to develop a simple operational model for the redistribution of pollutant fluxes within the intersection. This model has been further adapted to take account of the influence of fluctuations in wind direction over typical averaging periods. The resulting model is used in the street network model SIRANE.

Many towns and cities consist of similarly sized buildings in relatively regular arrangements with smaller scale roughness elements such as roofs, chimneys and balconies. The objective of this study is to investigate how small scale roughness elements modify the influence of the large scale organized roughness on the dispersion of a passive scalar in a turbulent boundary layer. Wind tunnel experiments were performed using a passive tracer released from a line source and concentration profiles were measured with a Flame Ionisation Detector. The measurements are compared with numerical solutions of the advection–diffusion equation. The results show that decreasing the cavity aspect ratio increases the turbulent vertical mass fluxes, and that the small scale roughness enhances these fluxes, but only in the skimming flow regime. Numerical simulations showed that outside the roughness sub-layer (RSL) the changes in surface roughness could be accounted for by a simple variation of the friction velocity, but inside the RSL the spatial variability of the flow imposed by the roughness elements has much more influence. A simple model for a spatially averaged dispersion coefficient in the RSL has been developed and is shown to agree satisfactorily with the concentrations measured in these experiments.

Flow in the urban boundary layer is strongly influenced by the surface roughness, which is composed principally of isolated buildings or groups of buildings. Previous research has shown that the flow regime depends on the characteristic height of these obstacles (H), and the spacing between them (W). In reality, the urban boundary layer contains roughness elements with a wide range of length scales; in many practical situations these can be classified into large-scale roughness—buildings, or groups of buildings—and small-scale roughness, such as street furniture and elements on the facades and roofs. It is important to understand how the small-scale roughness might modify mass and momentum transfer in the urban boundary layer, but relatively little information is available concerning the potential interaction between large- and small-scale roughness elements in the different flow regimes. This problem has been studied using wind-tunnel experiments, by measuring vertical velocity profiles over a two-dimensional obstacle array, adding small-scale roughness elements to the top of larger parallel square bars. The experiments were performed for different cavity aspect ratios: the results show that the small-scale roughness increases the turbulence intensities and the momentum transfer when the large-scale obstacles are closely packed (H/W > 1) but it has very little effect for more widely-spaced obstacles (H/W < 1).