Propagation of toxic substances in the urban atmosphere: A complex network perspective

The accidental or malicious release of toxic substances in the urban atmosphere is a major environmental and safety problem, especially in large cities. Computational fluid dynamics codes and simplified modelling tools have been used in the last decades to model pollutant dispersion in urban areas. These studies have shown that propagation is strongly influenced by the layout of buildings and, therefore, by the street topology of the city. This work presents a novel approach to the study of toxic propagation within the urban canopy based on the theory of complex networks. The urban canopy is modelled as a network, where the streets and the street intersections represent respectively the links and the nodes of the network. The direction and the weights of the links contain the geometrical characteristics of the street canyons and their wind conditions, so that all the key variables involved in pollutant dispersion are represented in a single mathematical structure that is a weighted and directed complex network. Thanks to this mathematical interpretation, propagation is modelled as a spreading process on a network and a depth-first search algorithm is used to rapidly delimit the zone of influence of a source node. This zone is the set of streets that are contaminated from the source. As a case study, the proposed model is applied to the urban tissue of the city of Lyon. The algorithm simulates a toxic release in all the nodes of the network and computes the number of people affected by each propagation process. In this way, the nodes with the most dangerous spreading potential are identified and vulnerability maps of the city are constructed. Moreover, various wind and concentration scenarios are easily implemented. The results highlight how the proposed method is effective in assessing the most vulnerable points in a city with a computational time that is up to three orders of magnitude lower than that of existing models. Moreover, the proposed approac

A METHODOLOGY TO CHARACTERISE THE SOURCES OF UNCERTAINTIES IN ATMOSPHERIC TRANSPORT MODELLING

The atmospheric dispersion modelling of pollutants is based on models, but also on data and users, who lead to uncertainties, i.e. to differences between the results of the models and the physical reality to describe. The question of the uncertainty of dispersion models is a subject of increasing interest for primarily two reasons: • In spite of the significant number of research works on atmospheric dispersion in the last 30 years, results of simulations preserve an important level of uncertainty. Since the reduction of this uncertainty will be more and more difficult, it thus seems today necessary to characterize it and, if possible, to quantify it. • The development of computer performances allows today the use of models in real time for decision-making aid, e.g. for the control of an industrial facility or for the management of an accident. In this context, where important decisions must be made quickly, it becomes extremely important to provide to the results of models an information on the uncertainty associated with these results. For better characterising uncertainties associated with atmospheric dispersion models, we propose a methodology of analysis which led us to make an inventory of all the sources of uncertainties of a model, considering all kind of models (Gaussian, Lagrangian, Eulerian). This methodology is based on a decomposition of the modelling process in four steps: • The collection of input data (sources, meteorology, topography, land cover…), with uncertainties in the measurement of these data, in their treatment and in their representativeness. • The modelling of the meteorological field, with uncertainties associated with intrinsic nature of atmospheric phenomena and with the quality of the models/approaches used to describe these phenomena. • The modelling of dispersion processes and of the physicochemical transformations. • The statistical treatment of results: it is shown that the choice of the output parameters (average annual or hourly maximum, maximum ground value or position of this maximum, etc.) modify, in an important way, the uncertainty of the results and how to evaluate it. The methodology proposed in this work should make it possible to progress towards a more systematic quantification of uncertainties associated with modelling of atmospheric dispersion

A METHODOLOGY TO CHARACTERISE THE SOURCES OF UNCERTAINTIES IN ATMOSPHERIC TRANSPORT MODELLING

The atmospheric dispersion modelling of pollutants is based on models, but also on data and users, who lead to uncertainties, i.e. to differences between the results of the models and the physical reality to describe. The question of the uncertainty of dispersion models is a subject of increasing interest for primarily two reasons: • In spite of the significant number of research works on atmospheric dispersion in the last 30 years, results of simulations preserve an important level of uncertainty. Since the reduction of this uncertainty will be more and more difficult, it thus seems today necessary to characterize it and, if possible, to quantify it. • The development of computer performances allows today the use of models in real time for decision-making aid, e.g. for the control of an industrial facility or for the management of an accident. In this context, where important decisions must be made quickly, it becomes extremely important to provide to the results of models an information on the uncertainty associated with these results. For better characterising uncertainties associated with atmospheric dispersion models, we propose a methodology of analysis which led us to make an inventory of all the sources of uncertainties of a model, considering all kind of models (Gaussian, Lagrangian, Eulerian). This methodology is based on a decomposition of the modelling process in four steps: • The collection of input data (sources, meteorology, topography, land cover…), with uncertainties in the measurement of these data, in their treatment and in their representativeness. • The modelling of the meteorological field, with uncertainties associated with intrinsic nature of atmospheric phenomena and with the quality of the models/approaches used to describe these phenomena. • The modelling of dispersion processes and of the physicochemical transformations. • The statistical treatment of results: it is shown that the choice of the output parameters (average annual or hourly maximum, maximum ground value or position of this maximum, etc.) modify, in an important way, the uncertainty of the results and how to evaluate it. The methodology proposed in this work should make it possible to progress towards a more systematic quantification of uncertainties associated with modelling of atmospheric dispersion

Urban aerosols survey LIDAR and numerical model

In this paper, we present a new methodology for urban aerosol survey, coupling Lidar measurements and numerical models. The aim of this study is build a continuous survey of aerosol impact on the local and regional scale

Poster: Toward a Better Monitoring of Air Pollution using Mobile Wireless Sensor Networks

International audienceMobile wireless sensor networks (MWSN) are widely used for monitoring physical phenomena such as air pollution where the aim is usually to generate accurate pollution maps in real time. The generation of pollution maps can be performed using either sensor measurements or physical models which simulate the phenomenon of pollution dispersion. The combination of these two information sources, known as data assimilation, makes it possible to better monitor air pollution by correcting the simulations of physical models while relying on sensor measurements. The quality of data assimilation mainly depends on the number of measurements and their locations. A careful deployment of nodes is therefore necessary in order to get better pollution maps. In this ongoing work, we tackle the placement problem of pollution sensors and design a mixed integer programming model allowing to maximize the assimilation quality while ensuring the connectivity of the network. We perform some simulations on a dataset of the Lyon city, France in order to show the eeectiveness of our model regarding the quality of pollution coverage

Urban air quality and meteorology on opposite sides of the Alps: The Lyon and Torino case studies

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

High resolution wind-tunnel investigation about the effect of street trees on pollutant concentration and street canyon ventilation

Greening cities is a key solution to improve the urban microclimate and mitigate the impact of climate change. However, the effect of tree planting on pollutant dispersion in streets is still a debated topic. To shed light on this issue, we present a wind-tunnel experiment aimed at investigating the effect of trees on street canyon ventilation. An idealized urban district was simulated by an array of blocks, and two rows of model trees were arranged at the sides of a street canyon oriented perpendicularly with respect to the wind direction. Reduced scale trees were chosen to mimic a realistic shape and aerodynamic behaviour. Three different spacings between the trees were considered. A passive scalar was injected from a line source placed at ground level and concentration measurements were performed in the whole canyon. Results show that the presence of trees alters the concentration pattern in the street with a progressive shift from a nearly two-dimensional to a three-dimensional field depending on tree density. Despite the significant change of the concentration field induced by trees, the average level of pollution in the street, and thus the overall ventilation efficiency, does not show a specific trend with the density of trees

Turbulent transfer and concentration statistics in a street canyon with tree planting

The exacerbation of the urban heat island due to global warming poses a serious risk to the health of citizens. Furthermore, the alteration of the urban microclimate affects air quality with an expected increase in the concentrations of harmful pollutants. Greening cities is an effective tool to mitigate these effects. However, the effect of tree planting in urban street canyons is still a debated topic. Despite their positive effect on temperature and their filtering action, trees can hinder air circulation thus limiting pollutant removal processes. In this context, it is essential to understand and model the effect of trees on the ventilation of street pollutants, heat and moisture . To this end, we present in this work the results of an experimental campaign conducted in a wind tunnel. An urban geometry with a street canyon perpendicular to the wind direction was reproduced. A linear source of passive scalar simulated the emission of pollutants from vehicular traffic. Reduced scale trees have been conceived to mimic a realistic aerodynamic behaviour. We investigated four different configurations of vegetation density: a street with no trees, two trees in the middle of the street, two rows of scattered trees and two dense rows of trees. Concentration and velocity measurements were performed in order to characterize the transfer processes of pollutants inside the street and to estimate a bulk vertical exchange rate. Results show that the presence of trees alters the concentration field in the street with a progressive shift from a nearly two-dimensional to a three-dimensional field. Despite the significant spatial variation in concentration, the presence of trees does not alter the overall efficiency of the ventilation as the vertical bulk exchange velocity remains almost constant in the different configurations. The statistical analysis of the turbulent concentration signal gives other insights in the transfer processes. The turbulent signal measured in different positions of the cavity and for different tree density follows a Gamma distribution with constant fluctuation intensity suggesting an almost universal behaviour within the canyon and providing a powerful modelling tool. Finally, combined measurements of concentration and velocity allows to measure the turbulent mass fluxes at the roof height and investigate their spectrum therefore enlightening the effect of trees on typical scales of motion

Evaluation of fast atmospheric dispersion models in a regular street network

The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (i) a Gaussian plume model, (ii) a Lagrangian stochastic model and (iii) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind direction and source location studied here, the strongest deviations from the LES reference were associated with mean over-predictions of concentrations by approximately a factor of 2 and with a relative scatter larger than a factor of 4 of the mean, corresponding to cases where the mean plume centreline also deviated significantly from the LES. This was linked to low accuracy of the underlying flow models/parameters that resulted in a misrepresentation of pollutant channelling along streets and of the uneven plume branching observed in intersections. The agreement of model predictions with the LES (which explicitly resolves the turbulent flow and dispersion processes) greatly improved by increasing the accuracy of building-induced modifications of the driving flow field. When provided with a limited set of representative velocity parameters, the comparatively simple street-network models performed equally well or better compared to the Lagrangian model run on full 3D wind fields. The study showed that street-network models capture the dominant building-induced dispersion processes in the canopy layer through parametrisations of horizontal advection and vertical exchange processes at scales of practical interest. At the same time, computational costs and computing times associated with the network approach are ideally suited for emergency-response applications

Leveraging the Potential of WSN for an Efficient Correction of Air Pollution Fine-Grained Simulations

International audienc