Atmospheric Pollutant Dispersion Research Articles

A hybrid CFD RANS/Lagrangian approach to model atmospheric dispersion of pollutants in complex urban geometries

Lagrangian atmospheric dispersion models consist of tracking the trajectories of particles of pollutant emitted into the atmosphere. In this paper, the objective is to compare the Lagrangian and Eulerian dispersion models in the same computational fluid dynamics code (Code Saturne), therefore using the same wind and turbulence fields for both. The Lagrangian stochastic model used in this work is the simplified Langevin model (SLM) of Pope (1985, 2000) and pertains to the approaches referred to as probability density function methods. This model has been extensively used in turbulent combustion or multiphase flows, but to our knowledge, it has not been used in atmospheric dispersion applications. First, we show that the SLM respects the well-mixed criterion. Then, we validate the model in the case of a continuous point release with uniform mean wind speed and turbulent diffusivity. Finally, we validate the model with an experimental campaign involving a stably stratified surface layer.

A New Direction in the Atmospheric Pollutant Dispersion inside the Planetary Boundary Layer

AbstractIn this study, an analytical solution for the steady-state fractional advection–diffusion equation was obtained to simulate the atmospheric dispersion of pollutants in a vertically inhomogeneous planetary boundary layer. The authors propose a method that uses the modified generalized integral Laplace transform technique to solve the transformed problem with a fractional derivative, resulting in a more general solution. The model results were compared with the fractional Gaussian model and demonstrate that, when considering an experimental dataset under moderately unstable conditions, fractional-derivative models perform better than traditional integer-order models.

Dispersion of atmospheric air pollution in summer and winter season

Seasonal variation of air pollution is associated with variety of seasons and specificity of particular months which form the so-called summer and winter season also known as the “heating” season. The occurrence of higher values of air pollution in different months of a year is associated with the type of climate, and accordingly with different atmospheric conditions in particular months, changing state of weather on a given day, and anthropogenic activity. The appearance of these conditions results in different levels of air pollution characteristic for a given period. The study uses data collected during a seven-year period (2009–2015) in the automatic measuring station of immissions located in Eastern Wielkopolska. The analysis concerns the average and maximum values of air pollution (i.e., particulate matter PM10, sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone) from the perspective of their occurrence in particular seasons and months or in relation to meteorological actors such as temperature, humidity, and wind speed.

The model SIRANE for atmospheric urban pollutant dispersion. PART III: Validation against NO2 yearly concentration measurements in a large urban agglomeration

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.

Simulation of trace metals and PAH atmospheric pollution over Greater Paris: Concentrations and deposition on urban surfaces

Urban areas can be subject not only to poor air quality, but also to contamination of other environmental media by air pollutants. Here, we address the potential transfer of selected air pollutants (two metals and three PAH) to urban surfaces. To that end, we simulate meteorology and air pollution from Europe to a Paris suburban neighborhood, using a four-level one-way nesting approach. The meteorological and air quality simulations use urban canopy sub-models in order to better represent the effect of the urban morphology on the air flow, atmospheric dispersion, and deposition of air pollutants to urban surfaces. This modeling approach allows us to distinguish air pollutant deposition among various urban surfaces (roofs, roads, and walls). Meteorological model performance is satisfactory, showing improved results compared to earlier simulations, although precipitation amounts are underestimated. Concentration simulation results are also satisfactory for both metals, with a fractional bias <0.5. Concentrations of benzo[a]pyrene are overestimated, probably because continental emissions may be overestimated. Concentrations of benzo[b]fluoranthene and indeno[1,2,3,cd]pyrene are underestimated, in part because of null boundary conditions. PAH deposition fluxes are consistent with earlier measurements obtained in the Greater Paris region. The model simulation results suggest that both wet and dry deposition processes need to be considered when estimating the transfer of air pollutants to other environmental media. Dry deposition fluxes to various urban surfaces are mostly uniform for PAH, which are entirely present in fine particles. However, there is significantly less wall deposition compared to deposition to roofs and roads for trace metals, due to their coarse fraction. Meteorology, particle size distribution, and urban morphology are all important factors affecting air pollutant deposition. Future work should focus on the collection of data suitable to evaluate the performance of atmospheric models for both wet and dry deposition with fine spatial resolution.

EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

Abstract. This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

Numerical study on effect of urban heating on local climate during calm inter-monsoon period in greater Kuala Lumpur, Malaysia

The Weather Research and Forecasting (WRF) mesoscale model is used to study the effect of urban heating on the local climate of the largest urban agglomeration of Malaysia, Greater Kuala Lumpur (GKL) during a period of weak synoptic forcing. Urbanization has induced a modelled daily mean urban heat island (UHI) intensity of 0.9°C with a more severe heating (1.9°C) at night. The diurnal wind field of GKL is greatly affected by the circulation of land/sea breeze. The immense heat generated in the city accelerates the moisture-bearing sea breeze during the day and the induced vertical lifting simultaneously creates a conducive environment for convective precipitation on the upwind region. The urban heating effect and surface roughness weakens the evening flow circulations in the region and potentially inhibits dispersion of heat and atmospheric pollutants. Simulation of UHI phenomenon is especially sensitive to the characterization of urban grids through sensitivity evaluation of numerous land use maps and urban canopy model (UCM) settings. When compared to observations, the WRF model best captures the urban heating phenomenon with updated land use map and calibrated single layer UCM, while the simple bulk UCM setting performs better than the default complex single layer UCM.

Fractional derivative models for atmospheric dispersion of pollutants

In the present work, we investigate the potential of fractional derivatives to model atmospheric dispersion of pollutants. We propose simple fractional differential equation models for the steady state spatial distribution of concentration of a non-reactive pollutant in Planetary Boundary Layer. We solve these models and we compare the solutions with a real experiment. We found that the fractional derivative models perform far better than the traditional Gaussian model and even better than models found in the literature where it is considered that the diffusion coefficient is a function of the position in order to deal with the anomalous diffusion.

The Message of “APEC Blue” for the Prevention and Control of Urban Air Pollution in China

Analysis of the meteorological conditions for atmospheric pollutant dispersion before and after the 2014 APEC meeting shows very significant effects of air pollution prevention and control measures on the meeting. It proves that the proper measures to control air pollution in the Beijing-Tianjin-Hebei Region are: establishing a regional emergency response mechanism to reduce emissions in the case of heavy air pollution, strengthening the local emergency response measures for emission reduction, and enhancing the early warning system for weather conditions conducive to heavy air pollution.

Microscale anthropogenic pollution modelling in a small tropical island during weak trade winds: Lagrangian particle dispersion simulations using real nested LES meteorological fields

Tropical islands are characterized by thermal and orographical forcings which may generate microscale air mass circulations. The Lesser Antilles Arc includes small tropical islands (width lower than 50 km) where a total of one-and-a-half million people live. Air quality over this region is affected by anthropogenic and volcanic emissions, or saharan dust. To reduce risks for the population health, the atmospheric dispersion of emitted pollutants must be predicted. In this study, the dispersion of anthropogenic nitrogen oxides (NOx) is numerically modelled over the densely populated area of the Guadeloupe archipelago under weak trade winds, during a typical case of severe pollution. The main goal is to analyze how microscale resolutions affect air pollution in a small tropical island. Three resolutions of domain grid are selected: 1 km, 333 m and 111 m. The Weather Research and Forecasting model (WRF) is used to produce real nested microscale meteorological fields. Then the weather outputs initialize the Lagrangian Particle Dispersion Model (FLEXPART). The forward simulations of a power plant plume showed good ability to reproduce nocturnal peaks recorded by an urban air quality station. The increase in resolution resulted in an improvement of model sensitivity. The nesting to subkilometer grids helped to reduce an overestimation bias mainly because the LES domains better simulate the turbulent motions governing nocturnal flows. For peaks observed at two air quality stations, the backward sensitivity outputs identified realistic sources of NOx in the area. The increase in resolution produced a sharper inverse plume with a more accurate source area. This study showed the first application of the FLEXPART-WRF model to microscale resolutions. Overall, the coupling model WRF-LES-FLEXPART is useful to simulate the pollutant dispersion during a real case of calm wind regime over a complex terrain area. The forward and backward simulation results showed clearly that the subkilometer resolution of 333 m is necessary to reproduce realistic air pollution patterns in this case of short-range transport over a complex terrain area. Globally, this work contributes to enrich the sparsely documented domain of real nested microscale air pollution modelling. This study dealing with the determination of the proper resolution grid and proper turbulence scheme, is of significant interest to the near-source and complex terrain air quality research community.

Modeling of Pollutant Dispersion in Atmosphere Based on Software Complex “SKAT”

The author of the article analyzes existing methods for calculation of pollutants’ dispersion in the atmosphere from a short continuous source under constant meteorological conditions. For this purpose the “SKAT” copyright software system elaborated by author was used. Furthermore, the author makes conclusions about advantages of using “Paskvilla method” for the calculation of gaseous substances’ dispersion from sources of this type.

Degenerate parabolic equations appearing in atmospheric dispersion of pollutants

Degenerate parabolic equations appearing in atmospheric dispersion of pollutants

Linkages Between Boundary-Layer Structure and the Development of Nocturnal Low-Level Jets in Central Oklahoma

In the Southern Great Plains, nocturnal low-level jets (LLJs) develop frequently after sunset and play an important role in the transport and dispersion of moisture and atmospheric pollutants. However, our knowledge regarding the LLJ evolution and its feedback on the structure of the nocturnal boundary layer (NBL) is still limited. In the present study, NBL characteristics and their interdependencies with LLJ evolution are investigated using datasets collected across the Oklahoma City metropolitan area during the Joint Urban field experiment in July 2003 and from three-dimensional simulations with the Weather Research and Forecasting (WRF) model. The strength of the LLJs and turbulent mixing in the NBL both increase with the geostrophic forcing. During nights with the strongest LLJs, turbulent mixing persisted after sunset in the NBL and a strong surface temperature inversion did not develop. However, the strongest increase in LLJ speed relative to the mixed-layer wind speed in the daytime convective boundary layer (CBL) occurred when the geostrophic forcing was relatively weak and thermally-induced turbulence in the CBL was strong. Under these conditions, turbulent mixing at night was typically much weaker and a strong surface-based inversion developed. Sensitivity tests with the WRF model confirm that weakening of turbulent mixing during the decay of the CBL in the early evening transition is critical for LLJ formation. The cessation of thermally-induced CBL turbulence during the early evening transition triggers an inertial oscillation, which contributes to the LLJ formation.

On the modeling of atmospheric pollutant dispersion during a diurnal cycle: A finite element study

In this paper, we present a numerical model to study pollutant dispersion in the atmospheric boundary layer (ABL). The model accounts for the mechanisms of advection by the mean wind in the horizontal direction, turbulent diffusion in the vertical direction to ground surface, dry deposition, and radioactive decay. More importantly, the model is capable of accounting for the evolution of the ABL structure over a diurnal cycle by considering parameterizations for the wind-speed and eddy-diffusivity profiles that depend on the atmospheric stability condition, which in turn undergoes dramatic changes throughout the day. To solve the resulting advection–diffusion equation, we propose a numerical method based on a stabilized finite element formulation. After validating the numerical model by simulating classical experiments and comparing its predictions with those available in literature, we study the dispersion of a pollutant during a full diurnal ABL cycle with the meteorological parameters generated by AERMET for a 24-h period on a 1-h basis.

Cumulative Impact Evaluation in Central Part of Liepaja with Comulative Pollution Index Method and Air Pollution Dispersion Modelling

Abstract Cumulative impact evaluation is one of the most actual problems in air quality monitoring. At the same time, it is also the most problematic factor to evaluate due to lack of appropriate methodology. The aim of this study was to assess the opportunity to use a new method – Cumulative Pollution Index (CPI) in cumulative impact calculation from two different sets of data – bioindication survey with Index of Atmospheric Purity method and air pollution dispersion modelling. Results show that the usage of modelling data, instead of measurements, in cumulative impact evaluation can be quite difficult due to the fact that dispersion models not always give sufficiently accurate data. Despite the issues with modelling specifics, the use of dispersion modelling in CPI calculation shows that the use of this approach not only gives plausible data – obtained values correlate with pollution level and forming strong clustering in spatial distribution, but also reveals new facts about cumulative impact – demonstrates the city microclimate importance in forming of cumulative effect due to geometry of street canyons.

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part I: Velocity and Concentration Measurements

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.

Modeling and Optimal Control of Atmospheric Pollution Hazard in Nuclear and Chemical Disasters

Nuclear and chemical disasters can cause heavy atmospheric pollution hazard and threat people's lives and health. In this paper, theory and application for modeling and optimal control of such hazard is studied. The modeling is based on the simulation and visualization of atmospheric dispersion of pollutants, the source term estimation of nuclear and chemical disasters, and the risk evaluation of hazardous substances. The optimal control is based on Natural Cybernetics theory, effective and economic cost evaluation of control techniques, and optimization methods. Some applications and illustrations of modeling and optimal control are reported.

Modelling Pollutant Dispersion in a Street Network

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.

Atmospheric dispersion modeling near a roadway under calm meteorological conditions

Atmospheric pollutant dispersion near sources is typically simulated by Gaussian models because of their efficient compromise between reasonable accuracy and manageable computational time. However, the standard Gaussian dispersion formula applies downwind of a source under advective conditions with a well-defined wind direction and cannot calculate air pollutant concentrations under calm conditions with fluctuating wind direction and/or upwind of the emission source. Attempts have been made to address atmospheric dispersion under such conditions. This work evaluates the performance of standard and modified Gaussian plume models using measurements of NO2, PM10, PM2.5, five inorganic ions and seven metals conducted near a freeway in Grenoble, France, during 11–27 September 2011. The formulation for calm conditions significantly improves model performance. However, it appears that atmospheric dispersion due to vehicle-induced turbulence is still underestimated. Furthermore, model performance is poor for particulate species unless road dust resuspension by traffic is explicitly taken into account.

The main principles of atmospheric diffusion modelling for regulatory purposes in Russia

This paper discusses the main principles of atmospheric diffusion modelling for regulatory purposes in Russia. They include the choice of air quality criteria, the development of universal models to calculate on a single base the dispersion of atmospheric pollutants from different types of source under unfavourable meteorological and topographical conditions, as well as experimental verification of the main theoretical results, and the development of practical recommendations for using the methods. Some results of the application of these principles to air pollution modelling in Russia are presented.