Three-Dimensional Modelling of Concentration Fluctuations in Complicated Geometry

The strong fluctuating component in the measured concentration time series of a dispersing gaseous pollutant in the atmospheric boundary layer, and the hazard level associated to short-term concentration levels, demonstrate the necessity of calculating the magnitude of turbulent fluctuations of concentration using computational simulation models. Moreover the computation of concentration fluctuations in cases of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In this paper, the formulation and evaluation of a model for concentration fluctuations, based on a transport equation, are presented. The model is applicable in cases of complex geometry. It is included in the framework of a computational code, developed for simulating the dispersion of buoyant pollutants over complex geometries. The experimental data used for the model evaluation concerned the dispersion of a passive gas in a street canyon between 4 identical rectangular buildings performed in a wind tunnel. The experimental concentration fluctuations data have been derived from measured high frequency concentrations. The concentration fluctuations model is evaluated by comparing the model's predictions with the observations in the form of scatter plots, quantile-quantile plots, contour plots and statistical indices as the fractional bias, the geometrical mean variance and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance in the present complex geometry case is satisfactory. The discrepancies between model predictions and observations are attributed to inaccuracies in prescribing the actual wind tunnel boundary conditions to the computational code.     

Modelling of concentrations along a moving observer in an inhomogeneous plume. Biological application: model of odour-mediated insect flights

We develop a stochastic model for the time-evolution of scalar concentrations and temporal gradients in concentration experienced by observers moving within inhomogeneous plumes that are dispersing within turbulent flows. In this model, scalar concentrations and their gradients evolve jointly as a Markovian process. Underlying the model formulation is a natural generalisation of Thomson’s well mixed condition [Thomson DJ (1987) J Fluid Mech 180:529–556]. As a consequence model outputs are necessarily compatible with statistical properties of scalars observed in experiment that are used here as model input. We then use the model to examine how insects aloft within the atmospheric boundary-layer can locate odour sources by modulating their flight patterns in response to odour cues. Mechanisms underlying odour-mediated flights have been studied extensively at laboratory-scale but an understanding of these flights over landscape scales is still lacking. Insect flights are simulated by combining the stochastic model with a simple model of insect olfactory response. These simulations show the strong influence of wind speed on the distributions of the times taken by insects to locate the source. In accordance with experimental observations [Baker TC, Vickers NJ (1997) In: Insect pheromone research: new directions, pp 248–264; Mafra-Neto A, Cardé RT (1994) Nature 369:142–144], flight patterns are predicted to become straighter and shorter, and source location is predicted to become more likely as the mean wind speed increases. The most probable arrival time to the source decreases with the mean wind speed. It is shown that scale-free movement patterns arising from olfactory-driven foraging stem directly from the power-law distribution of concentration excursion times above/below a threshold level and are robust with respect to variations in Reynolds number. Flight lengths are well represented by a power law distribution in agreement with the observed patterns of foraging bumblebees [Heinrich B (1979) Oecologia 40(3):235–245].     

The role of coherent turbulent structures in explaining scalar dissimilarity within the canopy sublayer

Scalar similarity is widely assumed in models and interpretation of micro-meteorological measurements. However, in the air space within and just above the canopy (the so-called canopy sublayer, CSL) scalar similarity is generally violated. The scalar dissimilarity has been mainly attributed to differences in the distribution of sources and sinks throughout the canopy. Since large-scale coherent structures in the CSL (e.g. double roller and sweep/ejection) arise from the instabilities generated by the interaction between the mean flow and the canopy, they may encode key dynamical features about the production term responsible for the source–sink dissimilarity of scalars. Therefore, it is reasonable to assume that the geometric attributes of coherent structures are tightly coupled to the onset and the vertical extent of scalar dissimilarity within the CSL. Large-eddy simulation (LES) runs were used to investigate the role of coherent structures in explaining scalar dissimilarity among three scalars (potential air temperature, water vapour and $\text{ CO }_2$ concentration) within the CSL under near-neutral conditions for horizontally uniform but vertically varying vegetation leaf area density. It was shown that coherent structures, when identified from the first mode of a novel proper orthogonal decomposition (POD) approach, were able to capture some features of the scalar dissimilarity in the original LES field. This skill was quantified by calculating scalar–scalar correlation coefficients and turbulent Schmidt numbers of the original field and the coherent structures, respectively. However, coherent structures tend to magnify the magnitude of scalar–scalar correlation, particularly in cases where this correlation is already strong. The ability of coherent structures to describe more complex features such as the scalar sweep-ejection cycle was also explored. It was shown that the first mode of the POD does not capture the relative importance of sweeps to ejections in the original LES field. However, the superposition of few secondary coherent structures, derived from higher order POD modes, largely diminish the discrepancies between the original field and the POD expansion.     

Subgrid-Scale Modeling of Reacting Scalar Fluxes in Large-Eddy Simulations of Atmospheric Boundary Layers

In large-eddy simulations of atmospheric boundary layer turbulence, the lumped coefficient in the eddy-diffusion subgrid-scale (SGS) model is known to depend on scale for the case of inert scalars. This scale dependence is predominant near the surface. In this paper, a scale-dependent dynamic SGS model for the turbulent transport of reacting scalars is implemented in large-eddy simulations of a neutral boundary layer. Since the model coefficient is computed dynamically from the dynamics of the resolved scales, the simulations are free from any parameter tuning. A set of chemical cases representative of various turbulent reacting flow regimes is examined. The reactants are involved in a first-order reaction and are injected in the atmospheric boundary layer with a constant and uniform surface flux. Emphasis is placed on studying the combined effects of resolution and chemical regime on the performance of the SGS model. Simulations with the scale-dependent dynamic model yield the expected trends of the coefficients as function of resolution, position in the flow and chemical regime, leading to resolution-independent turbulent reactant fluxes.     

Instantaneous transport of a passive scalar in a turbulent separated flow

The results of large-eddy simulations of flow and transient solute transport over a backward facing step and through a 180° bend are presented. The simulations are validated successfully in terms of hydrodynamics and tracer transport with experimental velocity data and measured residence time distribution curves confirming the accuracy of the method. The hydrodynamics are characterised by flow separation and subsequent recirculation in vertical and horizontal directions and the solute dispersion process is a direct response to the significant unsteadiness and turbulence in the flow. The turbulence in the system is analysed and quantified in terms of power density spectra and covariance of velocity fluctuations. The injection of an instantaneous passive tracer and its dispersion through the system is simulated. Large-eddy simulations enable the resolution of the instantaneous flow field and it is demonstrated that the instabilities of intermittent large-scale structures play a distinguished role in the solute transport. The advection and diffusion of the scalar is governed by the severe unsteadiness of the flow and this is visualised and quantified. The analysis of the scalar mass transport budget quantifies the mechanisms controlling the turbulent mixing and reveals that the mass flux is dominated by advection.     

Influence of the secondary motions on pollutant mixing in a meandering open channel flow

This paper presents large eddy simulation of turbulent flow in a meandering open channel with smooth wall and rectangular cross-section. The Reynolds number based on the channel height is 40,000 and the aspect ratio of the cross-section is 4.48. The depth-averaged mean stream-wise velocity agree well to experimental measurements. In this specific case, two interacting cells are formed that swap from one bend to the other. Transport and mixing of a pollutant is analysed using three different positions of release, e.g. on the inner bank, on the outer bank and on the centre of the cross section. The obtained depth-average mean concentration profiles are reasonably consistent with available experimental data. The role of the secondary motions in the mixing processes is the main focus of the discussion. It is found that the mixing when the scalar is released on the centre of the cross-section is stronger and faster than the mixing of the scalar released on the sides. When the position of release is close to a bank side, the mixing is weaker and a clear concentration of scalar close to the corresponding side-wall can be observed in both cases.     

Estimation method to identify scalar point source in turbulent flow based on Taylor’s diffusion theory

We introduce a new approach to diffusion-source estimation for quick identification of the unknown source, based on Taylor’s diffusion theory for turbulent transport of passive scalar from a fixed point source. In order to evaluate the method, we used planar laser-induced fluorescence to measure the concentration field of fluorescent dye in water flowing in a channel. We considered two kinds of datasets: basis data and observed data. The former is used to determine the basis functions characterizing the streamwise dependence of variances for three statistics: the mean concentration, root-mean-square (RMS) of fluctuations in the concentration, and RMS of the temporal gradient of the fluctuating concentration. Consistent with Taylor’s theory, we found that the lateral distribution of each statistic was basically Gaussian, and their standard deviations increased as a function of the square root of the distance from the emitted point. Based on these facts, a basis function can be formulated and expected to be valid for estimation of unknown sources. Source estimation was performed with the observed data, which corresponded to limited available information about the concentration from an unknown point source. We confirmed a good prediction accuracy of the proposed method with an averaged bias as small as the turbulent integral scale. Better precision was achieved by employing several statistics simultaneously. In this case, the standard deviation of the estimated source position was assessed at 14 % of the mean distance between the source and measurement points, after 100 source-estimate trials with different datasets. The methodology tested in this paper is expected to be applicable more general and complex environmental diffusion issues involving anisotropic turbulent dispersion, and space–time variable mainstream systems; but its versatility in such systems is currently under investigation.     

Embedded large eddy simulation approach for pollutant dispersion around a model building in atmospheric boundary layer

In the present article, the potential of embedded large eddy simulation (ELES) approach to reliably predict pollutant dispersion around a model building in atmospheric boundary layer is assessed. The performance of ELES in comparison with large eddy simulation (LES) is evaluated in several ways. These include a number of qualitative and quantitative comparisons of time-averaged and instantaneous results with wind tunnel measurements supplemented by statistical data analyses using scatter plots and standard evaluation metrics. Results obtained by both LES and ELES approaches show very good agreement with the experiment. However, addition of turbulence to mean flow at Reynolds averaged Navier–Stokes (RANS)–LES interface in ELES approach not only increases the turbulence intensity, it also results in larger values of turbulent kinetic energy (TKE) as well as a shorter reattachment length in the wake region. Accordingly, higher levels of TKE predicted by ELES increase the local intensity of concentration leading to shorter plume shapes as compared with LES. In general, ELES shows better agreement with experiment on the surfaces of model building and also in the downstream wake region. In terms of computational costs, the CPU time required to obtain statistical values in ELES is about 49 % lower than that of LES and the number of iterations per time step is also reduced by 55 % as compared with LES.     

Effects of the Resolution and Kinematics of Olfactory Appendages on the Interception of Chemical Signals in a Turbulent Odor Plume

A variety of animals use olfactory appendages bearing arrays of chemosensory neurons to detect chemical signatures in the water or air around them. This study investigates how particular aspects of the design and behavior of such olfactory appendages on benthic aquatic animals affect the patterns of intercepted chemical signals in a turbulent odor plume. We use virtual olfactory `sensors' and `antennules' (arrays of sensors on olfactory appendages) to interrogate the concentration field from an experimental dataset of a scalar plume developing in a turbulent boundary layer. The aspects of the sensors that we vary are: (1) The spatial and temporal scales over which chemical signals arriving at the receptors of a sensor are averaged (e.g., by subsequent neural processing), and (2) the shape and orientation of a sensor with respect to ambient water flow. Our results indicate that changes in the spatial and temporal resolution of a sensor can dramatically alter its interception of the intermittency and variability of the scalar field in a plume. By comparing stationary antennules with those sweeping through the flow (as during antennule flicking by the spiny lobster, Panulirus argus), we show that flicking alters the frequency content of the scalar signal, and increases the likelihood that the antennule encounters peak events. Flicking also enables a long, slender (i.e., one-dimensional) antennule to intercept two-dimensional scalar patterns.     

Numerical modelling of horizontal sediment-laden jets

Sediment-laden turbulent flows are commonly encountered in natural and engineered environments. It is well known that turbulence generates fluctuations to the particle motion, resulting in modulation of the particle settling velocity. A novel stochastic particle tracking model is developed to predict the particle settling out and deposition from a sediment-laden jet. Particle velocity fluctuations in the jet flow are modelled from a Lagrangian velocity autocorrelation function that incorporates the physical mechanism leading to a reduction of settling velocity. The model is first applied to study the settling velocity modulation in a homogeneous turbulence field. Consistent with basic experiments using grid-generated turbulence and computational fluid dynamics (CFD) calculations, the model predicts that the apparent settling velocity can be reduced by as much as 30 % of the stillwater settling velocity. Using analytical solution for the jet mean flow and semi-empirical RMS turbulent velocity fluctuation and dissipation rate profiles derived from CFD predictions, model predictions of the sediment deposition and cross-sectional concentration profiles of horizontal sediment-laden jets are in excellent agreement with data. Unlike CFD calculations of sediment fall out and deposition from a jet flow, the present method does not require any a priori adjustment of particle settling velocity.     

Sensitivity of air quality model prediction to parameterization of vertical eddy diffusivity

This paper investigates the effects of vertical eddy diffusivities derived from the 3 different planetary boundary layer (PBL) schemes on predictions of chemical components in the troposphere of East Asia. Three PBL schemes were incorporated into a regional air quality model (RAQM) to represent vertical mixing process and sensitivity simulations were conducted with the three schemes while other options are identical. At altitudes <2km, all schemes exhibit similar skill for predicting SO₂ and O₃, but more difference in the predicted NO_x concentration. The Gayno–Seaman scheme produces the smallest vertical eddy diffusivity (Kz) among all schemes, leading to higher SO₂ and NO_x concentrations near the surface than that from the other 2 schemes. However, the effect of vertical mixing on O₃ concentration is complex and varies spatially due to chemistry. The Gayno–Seaman scheme predicts lower O₃ concentrations than the other two schemes in the parts of northern China (generally VOC-limited) and higher ones in most parts of southern China (NO_x-limited). The Byun and Dennis scheme produces the largest mixing depth in the daytime, which bring more NO_x into upper levels, and the mixing depth predicted by the Gayno–Seaman scheme is the smallest, leading to higher NO_x and lower O₃ concentrations near the surface over intensive emission regions.     

Lagrangian models of dispersion in marine environment

Turbulent dispersion can be studied successfully by using Lagrangian particle models. In general, the prediction of correct concentration fields is a complex issue when the turbulent field is inhomogeneous and non-stationary. Two classes of Lagrangian dispersion models have been considered in this work, which are based on the Wiener process and the so called “well-mixed” criterion. In order to test the performances of these models and shed light on the underlying physical processes and modeling assumptions, four different numerical models have been compared and tested by means of their long time behavior by considering several study cases concerning idealized marine environment. Furthermore, the coupling of the community model Princeton Ocean Model (POM) with the Lagrangian model LASEMOD (LAgrangian SEa MODel) is used to investigate the temporal and spatial evolution of a passive pollutant released in the vicinity of the coast in the Tyrrhenian Sea basin. The simulation shows with reasonable accuracy the time evolution of both the hydrodynamic and the concentration fields and provides a useful insight into the evaluation of the environmental impact of pollutant releases along the coast.     

Prediction of pollutant dispersion in turbulent two-phase flows

With a growing awareness of water pollution problems, in recent years there has been a considerable increased effort in developing and applying numerical models to predict accurately the contaminant distributions, particularly in free surface flows. This numerical study presents a predictive hydrodynamic model in order to explore the dispersion phenomenon of a pollutant injected from time-dependent sources in a turbulent free surface flow. More precisely, we study the impact of pulsation on the dispersion of an injected material. The air/water interface was modeled with the volume of fluid method and sharpness of the free surface was assured by means of Geo-Reconstruct scheme. The numerical results showed that the pulsation played a dominant role at the early stage of the pollutant transport. It was also observed that the pulsation affected the distribution of the injected material especially near the front and that a major swirling action was developed compared to the constant-rate-injection case.     

Air quality and PM10-associated poly-aromatic hydrocarbons around the railway traffic area: statistical and air mass trajectory approaches

Diesel engine railway traffic causes atmosphere pollution due to the exhaust emission which may be harmful to the passengers as well as workers. In this study, the air quality and PM₁₀ concentrations were evaluated around a railway station in Northeast India where trains are operated with diesel engines. The gaseous pollutant (e.g. SO₂, NO₂, and NH₃) was collected and measured by using ultraviolet–visible spectroscopy. The advanced level characterizations of the PM10 samples were carried out by using ion chromatography, Fourier-transform infrared, X-ray diffraction, inductively coupled plasma optical emission spectrometry , X-ray photoelectron spectroscopy, field-emission scanning electron microscopy with energy-dispersive spectroscopy, and high-resolution transmission electron microscopy with energy-dispersive spectroscopy techniques to know their possible environmental contaminants. High-performance liquid chromatography technique was used to determine the concentration of polycyclic aromatic hydrocarbons to estimate the possible atmospheric pollution level caused by the rail traffic in the enclosure. The average PM₁₀ concentration was found to be 262.11 µg m⁻³ (maximum 24 hour) which indicates poor air quality (AQI category) around the rail traffic. The statistical and air mass trajectory analysis was also done to know their mutual correlation and source apportionment. This study will modify traditional studies where only models are used to simulate the origins.

     

Analysis and prediction of the influence of energy utilization on air quality in Beijing

This work evaluates the influence of energy consumption on the future air quality in Beijing, using 2000 as the base year and 2008 as the target year. It establishes the emission inventory of primary PM₁₀, SO₂ and NO_x related to energy utilization in eight areas of Beijing. The air quality model was adopted to simulate the temporal and spatial distribution of each pollutant concentration in the eight urban areas. Their emission, concentration distribution, and sectoral share responsibility rate were analyzed, and air quality in 2008 was predicted. The industrial sector contributed above 40% of primary PM₁₀ and SO₂ resulting from energy consumption, while vehicles accounted for about 65% of NO_x. According to the current policy and development trend, air quality in the eight urban areas could become better in 2008 when the average concentrations of primary PM₁₀, SO₂ and NO₂ related to energy utilization at each monitored site are predicted to be about 25, 50 and 51 μg/m³, respectively.     

Anti-diffusion and source identification with the ‘RAW’ scheme: A particle-based censored random walk

This paper presents a novel methodology for time reversal in advective-diffusive pollutant transport in groundwater systems and other environmental flow systems (specifically: time reversal of diffusive terms). The method developed in this paper extends previous particle-based approaches like the Reversed Time Particle Tracking Method of Bagtzoglou [6]. The reversal of the ‘diffusive’ and/or ‘macrodispersive’ component of pollutant migration is especially under focus here. The basis of the proposed scheme for anti-diffusion is a continuous time, censored, non-local random walk capable of tracking groundwater solute concentration profiles over time while conserving the (reverse) Fickian properties of the anti-diffusing particle cloud in terms of moments. This scheme is an alternative to the direct solution of the eulerian concentration-based diffusion PDE, which is notoriously unstable in reverse time. Our analysis leads to the conclusion that an adaptive time stepping scheme—with decreasing time step—is necessary in order to maintain a constant amount of anti-diffusion (the reverse form of Fick’s law). Specifically, we study the relations between the following parameters: time step evolution vs. time (or vs. number of steps); variance evolution (decrease rate); total time (or number of steps) required to reach a fully anti-diffused solution. The proposed approach is shown to be quite efficient; typically, for every ten time steps, one to two orders of magnitude reduction of the dispersion width of the plume can be attained. Furthermore, the method is shown to be asymptotically exact for reverse Fickian diffusion. The method is applied with success to several situations involving the diffusive transport of a conservative solute in the following cases: (i) Single source recovery in one-dimensional space with constant diffusion parameters (this example serves as a validation test for the theory); (ii) Single source recovery in two-dimensional space with constant isotropic diffusion (this example also serves as a test for the theory); (iii) Multiple source recovery in two-dimensional space, assuming isotropic diffusion. It is expected that the methodology tested in this paper is applicable more generally to complex environmental pollution problems involving multiple sources, anisotropic hydrodynamic dispersion, and space-time variable advection-diffusion flow systems; the modeling of reverse diffusion/dispersion in such systems is currently under investigation.     

Large-eddy simulation of low-level jet-like flow in a canopy

The computational method of Large-Eddy Simulations has been used to study the weak, neutrally stable drainage flow within tree canopies. The computational results show that a secondary velocity maximum that resembles a jet is formed within the canopy under the nocturnal flow conditions. This jet-like flow is important in the analysis and measurements of the net ecosystem-atmosphere exchange (NEE) for carbon dioxide (CO₂). A uniformly distributed, plane source was placed within the canopy in order to simulate the nocturnal production of CO₂. The NEE is calculated as the sum of the integration of the rate of change of the concentration of CO₂ over the computational domain, the vertical turbulent flux measured directly by eddy-covariance (EC) method, and the advection terms, which are not taken into account in the EC method. Numerical results of the velocity and concentration fields, within and above the canopy, are presented and their impact on the CO₂ transport is investigated in detail. The computational results show that 15–20% of NEE is drained out by the advection process under the canopy. The results also show that the turbulent fluctuations in the lateral direction are also significant and may result in 2–5% CO₂ transport.     

An assessment of the air pollution data from two monitoring stations in Kuwait

This article assesses the air pollution data from two monitoring stations in Kuwait. The measurements cover major pollutants, i.e., CO, CO₂, methanated and non-methanated hydrocarbons, NO _x , SO₂, O₃, and particulate matter (PM10). The data also includes meteorological parameters, i.e., solar intensity, temperature, wind speed, and wind direction, and has been collected over a period 4 years, from 2001 to 2004. Data analysis includes the assessment of annual hourly averages and 1-h maxima. Typical pollutant concentration trends, similar to those previously reported for Kuwait and for other locations around the world, are observed except for particulate matter measurements, which have higher values because of proximity to the desert. Emissions of nitrogen oxides show a consistent increase over the years. This is caused by the increase in the number of motor vehicles and the expansion in power generation and industrial activities. The data collected is a subset of the air quality criteria, as defined by the US EPA (United States Environmental Protection Agency).     

Advanced integral model for groups of interacting round turbulent buoyant jets

An integral model that combines all advantages of Superposition Method (SM), Entrainment Restriction Approach (ERA) and Second Order Approach (SOA) is proposed to predict the mean axial velocity and concentration fields of a group of N interacting vertical round turbulent buoyant jets. SM is successful in predicting the fields of mean axial velocity and mean concentration for a group of N interacting jets or plumes and ERA is advantageous in predicting the above fields for either two or large number (N → ∞) of interacting buoyant jets in the whole range of buoyancy. SOA takes into consideration in a dynamic way the turbulent contribution to the momentum and buoyancy fluxes and provides better accuracy than the usual procedures. A novelty of the proposed model is the production and utilisation of advanced profile distributions, convenient for the mean axial velocities and concentrations in a cross-section of the entire group of buoyant jets. These profiles are developed on the basis of flux conservation of momentum, buoyancy and kinetic energy for the mean motion. They enhance dynamic adaptation of the individual buoyant jet axes to the group centreline. Due to these profile distributions, the present model owns generality of application and better accuracy of predictions compared to usual integral models using simple Gaussian or top-hat profiles; thus it conferred the name Advanced Integral Model (AIM). AIM is herein applied to predict the mean flow properties of two different arrangement types of any number of buoyant jets: (a) linear diffusers and (b) rosette-type risers. Present results are compared to available experimental data and traditional solutions based on Gaussian profiles. Findings may be useful for design purposes and environmental impact assessment.     

Analysis of air pollution at Shuaiba industrial area in Kuwait

A study has been conducted over a period of one year on measurements of air pollution in the Shuaiba Industrial Area (SIA) of Kuwait. The study included analysis of pollutant behaviour relative to the wind speed and direction. SIA comprises several large scale industries including three petroleum refineries, two power plants, two fertilizer plants, a cement plant, a chlorine and soda plant, a commercial harbour and two large oil loading terminals. Measurements of 15 parameters have been carried out every 5 minutes using a mobile laboratory fitted with an automatic calibrator and a data storage system. The pollutants studied include methane, non‐methane hydrocarbons (NMHC), carbon monoxide, carbon dioxide, nitrogen oxides (NO, NO₂, and NO _x ), sulphur dioxide, ozone and suspended dust. Meteorological parameters monitored simultaneously include wind speed and direction, air temperature, relative humidity, solar radiation, and barometric pressure. The air quality data collected using the mobile laboratory have been used to calculate the diurnal and monthly variations in the major primary and secondary pollutants. Distribution levels of these pollutants relative to wind direction and speed have also been used in the analysis. The results show large diurnal variations in some pollutant concentrations. Generally, two types of concentration variations have been found, depending on whether the species is a primary or a secondary pollutant. Diurnal variations with two maxima were observed in the concentrations of primary pollutants including NO, SO₂, NMHC, CO and suspended dust, whereas a single maximum was observed for secondary pollutants such as O₃and NO₂. The monthly variations of SO₂and NO _x showed maximum values during the warm months. However, ozone showed a quite marked seasonal variation with maxima during spring and late summer and a minimum during the early summer. The results also indicated a common source for NO _x , SO₂, NMHC, CO and suspended dust to the North‐West (NW) of the monitoring station. Moreover for NO _x and SO₂, another less significant source is to the South‐South‐West (SSW) and South‐West (SW) of the monitoring station.