Simulation Of Pollutant Dispersion Research Articles

On the accuracy of idealized sources in CFD simulations of pollutant dispersion in an urban street canyon

Idealized pollutant sources are widely used by the scientific community to replicate traffic emissions in wind tunnel tests and CFD simulations. However, it is unclear to what extent such idealized sources can adequately reproduce the emission and dispersion by cars in idle (static) or moving situations in streets. This study investigates the impact of a static idealized point source (S-IPS) versus an idling or static (S-) and a moving or dynamic (D-) realistic car source (RCS) on the pollutant dispersion in a street canyon. First, 3D steady RANS and LES simulations are performed with a S-IPS and validated by means of wind-tunnel tests. Next, LES simulations are performed to analyze the impact of S-IPS versus S-RCS. Finally, three D-RCS with different car speeds are simulated and compared with S-RCS. The results show that using a S-RCS increases the plane-averaged concentration by 11%–140 % at z/H = 0.03 and by 30%–50 % at y/H = 0, with respect to S-IPS. The comparison of S-RCS and D-RCS shows that car movement can also have a large impact on pollutant dispersion along the canyon.

Large-Eddy Simulation of Turbulent Airflow and Pollutant Dispersion from a Ground-level Point-Source in a Model Urban Area

Large-Eddy Simulation of Turbulent Airflow and Pollutant Dispersion from a Ground-level Point-Source in a Model Urban Area

Assessment on fast simulation of wind-driven pollutant dispersion around a street canyon with regime-switching Markov chain

High-density cities shorten commutes but also create proximity to air pollution sources. Sensors coupled with simulations can achieve real-time monitoring and risk assessment, and the recently emerging data-driven models provide opportunities that allow minimizing the computation burden of physical models. This study investigates the use of a time inhomogeneous Markov chain (CLF-MC) to fast simulation of wind-driven pollutant dispersion around a street canyon. The CLF-MC model is trained and tested using synthetic datasets obtained from large eddy simulations (LES). The LES model is validated using a benchmark wind tunnel test, which yields correlation coefficients above 0.95. The results show that the CLF-MC can faithfully reproduce the cumulative distribution of air pollution concentrations at the receptor site using the optimal model configuration identified in this study. For the hold-out test dataset, the release condition is a time-varying release strength, and the CLF-MC shows improved prediction results compared to the baseline models, i.e. the weighted average deviation is 15 % and 51 % smaller, respectively. In comparison to LES, the CLF-MC model is 4.8 × 106 times faster. These findings provide scientific references for fast and accurate wind-driven pollutant dispersion simulation using the probabilistic modelling approach.

Hydrodynamic modelling and simulation of the variation of the water quality parameters of the Bahlui River

For the simulation of hydrodynamic changes and pollutant dispersion in the study area, an appropriate model was applied using the DHI series software. Flows were modelled using the hydrodynamic model and the hydrological model, and water quality was modelled using MIKE 11 ECO LAB. The paper presents a simulation for the water quality of the Bahlui River. Mike 11 contains a GIS map and simulation editors. Water quality parameters such as temperature, dissolved oxygen and biochemical oxygen demand were simulated. Modelling results can be used as a planning tool to help decision makers during different phases.

Realistic simulation of air pollution in an urban area to promote environmental policies

Visualizing tools are now capable of synthesizing satellite imagery with Computational Fluid Dynamics (CFD) results. The new method is applied in Augsburg, Germany, and consists of two main phases: pre-processing and post-processing. The pre-processing phase involves creating geometry, mesh, and extracting results from simulations of traffic pollutant dispersion. In the post-processing phase, the results are combined with satellite images to produce visually optimized results. The demonstration of road traffic air pollution is based on real data from local air quality measurements and specific scenarios. The results indicate that using these visualization tools produce understandable and impressive images and videos. This enhances the public's comprehension of scientific results and raises awareness of environmental issues. An increased understanding of scientific results can reinforce the implementation of environmental policies by pressuring responsible authorities to take action. This paper provides a valuable tool for visualizing air pollution and facilitating public engagement with environmental issues.

CFD simulation of pollutant dispersion using anisotropic models: Application to an urban like environment under neutral and stable atmospheric conditions

Modeling the atmospheric dispersion of pollutants emitted from different types of sources under various atmospheric conditions is an essential prerequisite for risk assessment studies and emergency preparedness. In this study, we evaluate the performance of different turbulence models and velocity-scalar correlation models implemented in the Code_Saturne. The evaluation is done with observations of four trial cases of the Mock Urban Setting Test (MUST) campaign in an urban type environment and in neutral and stable atmospheric conditions. For all of the trials studied, the CFD model with a first-order closure model (k−ɛ) predicts 61.1% of the concentrations within a factor of two of the observations, which is higher than the percentage of predicted points (58.8%) when a second-order closure model (Rij−ɛ) is used. Overall, the CFD model underestimates observed concentrations, regardless of the turbulence model used. For the trial with slightly stable conditions, the results show that the k−ɛ model combined with an algebraic SGDH model predicts 75% concentrations within a factor of two of the observations. The performance of the k−ɛ model is compared to that of the Rij−ɛ model when used with the algebraic SGDH, GGDH models and with the scalar flux transport equation (DFM model). Under slightly stable atmospheric conditions, the DFM model predicts 69% of concentrations within a factor of two of observations, showing promise for modeling under these conditions, despite its relatively high computational cost.

A System Coupled GIS and CFD for Atmospheric Pollution Dispersion Simulation in Urban Blocks

Atmospheric pollution is a critical issue in public health systems. The simulation of atmospheric pollution dispersion in urban blocks, using CFD, faces several challenges, including the complexity and inefficiency of existing CFD software, time-consuming construction of CFD urban block geometry, and limited visualization and analysis capabilities of simulation outputs. To address these challenges, we have developed a prototype system that couples 3DGIS and CFD for simulating, visualizing, and analyzing atmospheric pollution dispersion. Specifically, a parallel algorithm for coordinate transformation was designed, and the relevant commands were encapsulated to automate the construction of geometry and meshing required for CFD simulations of urban blocks. Additionally, the Fluent-based command flow was parameterized and encapsulated, enabling the automatic generation of model calculation command flow files to simulate atmospheric pollution dispersion. Moreover, multi-angle spatial partitioning and spatiotemporal multidimensional visualization analysis were introduced to achieve an intuitive expression and analysis of CFD simulation results. The result shows that the constructed geometry is correct, and the mesh quality meets requirements with all values above 0.45. CPU and GPU parallel algorithms are 13.3× and 25× faster than serial. Furthermore, our case study demonstrates the developed system’s effectiveness in simulating, visualizing, and analyzing atmospheric pollution dispersion in urban blocks.

Reduced-order modeling for parameterized large-eddy simulations of atmospheric pollutant dispersion

Mapping near-field pollutant concentration is essential to track plume dispersion in urban areas. By solving most of the turbulence spectrum, large-eddy simulations (LES) can accurately represent concentration spatial variability. Synthesizing this large amount of information to improve the accuracy of lower-fidelity operational models is particularly appealing. Due to the computational cost of LES, it becomes a challenge in multi-query contexts, to quantify how tracer dispersion changes with atmospheric and source parametric variations. We propose a data-driven reduced-order model (ROM) combining proper orthogonal decomposition (POD) and probabilistic Gaussian process regression (GPR) to efficiently predict tracer concentration field first- and second-order statistics. The novelty of this work lies in the original approach used to efficiently tune the GPR based on the available reduced-basis information and properties. In practice, the GPR hyperparameters are optimized through the hierarchy of POD modes thanks to Bayesian optimization informed by POD. The robustness of the approach is also addressed under small data constraint. A detailed analysis of our model performance is carried out in the case of a turbulent atmospheric boundary-layer flow over a surface-mounted obstacle for which the convective character of the system together with the uncertainty of the pollutant source location make it very challenging for ROM. The model is able to capture the wide range of spatial scales across the POD modes. The ROM accuracy remains acceptable for a minimal budget of about one hundred LES snapshots, providing a first estimation moving towards more realistic atmospheric dispersion applications.

CFD simulation of pollutant dispersion in a street canyon: Impact of idealized and realistic sources

Pollutant dispersion is of great relevance for people living in urban areas. High levels of pollutant can usually result from the combination of poor natural ventilation and high-traffic volumes of vehicles. Idealized point and line sources are commonly used to reproduce traffic emissions in simplified portions of urban areas, as street canyons. However, a limited number of studies focuses on the usage of realistic sources, as real car geometries which can influence the flow characteristics and the pollutant distribution inside the canyon. This is also the goal of the present paper for which Computational Fluid Dynamics (CFD) simulations were performed by means of scale-adaptive simulation (SAS) on a street canyon to investigate the impact of idealized and realistic sources. In stage 1, SAS simulations were performed with idealized line sources by reproducing reduced-scale wind-tunnel (WT) experiments. In stage 2, SAS simulations were carried out on a street canyon using idealized line sources and realistic sources with different levels of simplification. The results showed that the use of realistic sources can result in an increased concentration of 1.03 - 6.76 (at z = 0.33 m above the ground), with respect to the use of idealized line sources. Overall, at the lower level of the street canyon (e.g. z < 1.5 m), the concentration can be strongly affected by the presence of the car bodies. The results of the present study are expected to help urban planners as well as governmental institutions to reduce pollutant concentrations in the street canyon.

Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion

This paper presents a framework for the development of a computationally-efficient surrogate model for air pollution dispersion. Numerical simulation of air pollution dispersion is of fundamental importance for the mitigation of pollution in Seveso-type accidents, and, in extreme cases, for the design of evacuation scenarios for which long-range forecasting is necessary. Due to the high computational load, sophisticated simulation programs are not always useful for prompt computational studies and experimentation in real time. Surrogate models are data-driven models that mimic the behaviour of more accurate and more complex models in limited conditions. These models are computationally fast and enable efficient computer experimentation with them. We propose two methods. The first method develops a grid of independent dynamic models of the air pollution dispersion. The second method develops a reduced grid with interpolation of outputs. Both are demonstrated in an example of a realistic, controlled experiment with limited complexity based on an approximately 7 km radius around the thermal power plant in Šoštanj, Slovenia. The results show acceptable matching of behaviour between the surrogate and original model and noticeable improvement in the computational load. This makes the obtained surrogate models appropriate for further experimentation and confirms the feasibility of the proposed method.

VGEs as a New Platform for Urban Modeling and Simulation

The complexity of interrelationships between urban natural environments and human environments is increasing with rapid urbanization. This brings new challenges to urban modeling and simulation in simultaneously meeting the comprehensive needs of the dual integration of data and models, multi-type visualizations, human-centered simulation, geographic collaboration, and interactions between physical and virtual spaces. We here propose virtual geographic environments (VGEs) as a new platform of urban modeling and simulation. After discussing the evolution, definition, and features of VGEs, we design a VGE framework for urban system modeling and simulation. Two typical cases are provided to illustrate how VGEs support urban modeling and simulation on different scales: VGE-based collaborative modeling and the simulation of air pollution dispersion in the Pearl River Delta (PRD) urban agglomeration, and fire emergency crowd evacuation simulation. In the future, VGEs may also play an important role in digital twin cities and urban metaverses.

Large-Eddy Simulation of Airflow and Pollutant Dispersion in a Model Street Canyon Intersection of Dhaka City

The atmospheric flow and dispersion of traffic exhaust were numerically studied in this work while considering a model street canyon intersection of a city. The finite volume method (FVM)-based large-eddy simulation (LES) technique in line with ANSYS Fluent have been used for flow and pollutant dispersion modelling through the consideration of the atmospheric boundary layer (ABL). Hexahedral elements are considered for computational domain discretization in order to numerically solve problems using FVM-LES. The turbulence parameters were superimposed through a spectral synthesizer in the existing LES model through ANSYS Fluent as part of ’damage control’ due to the unsteady k−ϵ simulation. Initially, the code is validated with an experimental study of an urban street canyon where the width and height ratio is in unity. After validation, a model urban street canyon intersection was investigated in this work. The model shows a high pollutant concentration in the intersecting corner areas of the buildings. Additionally, the study of this model intersection shows a high level of pollutant concentration at the leeward wall of downwind building in the case of increased height of an upwind building. Most importantly, it was realized from the street intersection design that three-dimensional interconnection between the dominating canyon vortices and roof level flow plays a pivotal role in pollutant concentration level on the windward walls. The three-dimensional extent of corner eddies and their interconnections with dominating vortices were found to be extremely important as they facilitate enhanced ventilation. Corner eddies only form for the streets towards the freeway and not for the streets towards the intersection. The results and key findings of this work offer qualitative and quantitative data for the estimation, planning, and implementation of exposure mitigation in an urban environment.

Development of a micro-in-meso-scale framework for simulating pollutant dispersion and wind environment in building groups

Simulation of pollutant dispersion and wind environment is of significant importance to the safety and health of pedestrians and residents. However, the high threshold of data collection and model configuration has hindered its application in the building industry. To address the problem, this paper proposes a Micro-in-Meso-scale (MiM) simulation framework for automatic and foolproof pollutant dispersion and wind environment simulation. The meso-scale Weather Research and Forecast (WRF) model is first carried out to obtain city-level meteorology data with sufficient resolution. The micro-scale Computational Fluid Dynamics (CFD) model is then initialized to simulate pollutant dispersion and wind environment in building groups. The two models are coupled where the numerical results of WRF are provided to CFD for the configuration of boundary conditions. Fluid dynamics knowledge and spatial characteristics of building groups are also embedded in the model to lower the threshold of performing atmospheric simulations. A Geographic Information System (GIS)-based data management module is established simultaneously to achieve automatic collection, processing and management of raw data for simulation. The conversion algorithm of GIS data is further implemented to achieve the automatic generation of the CFD domain. Finally, the framework is developed to embed the data module and simulation module, and provide an easy-to-operate environment for building industry personnel. The framework is validated by data of actual building groups in four major cities in China. The test results illustrate the efficiency and feasibility of the platform. The study is expected to enhance the application of wind environment simulation in building industries.

Simulation of Traffic-Born Pollutant Dispersion and Personal Exposure Using High-Resolution Computational Fluid Dynamics

Road vehicles are a large contributor to nitrogen oxides (NOx) pollution. The routine roadside monitoring stations, however, may underrepresent the severity of personal exposure in urban areas because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at a local level. This study deploys a 10-cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at a constant speed may generate momentary roadside concentrations of NOx as high as 1.25 mg/m3, with a 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

Quantifying the Impact of Alternative Bus Stop Platforms on Vehicle Emissions and Individual Pollution Exposure at Bus Stops.

Due to stop-and-go events, bus stops are often treated as “hot spots” for air pollution. The design of bus stops should be optimized to reduce emissions and exposure for transit commuters. The objective of this study was to analyze the impact of bus stop platform types on vehicle emissions and individual pollution exposure. Second-by-second emissions data were first collected from one bus using a portable emission measurement system (PEMS). Microscopic traffic simulation was then used to estimate overall traffic emissions under six scenarios with different bus stop settings. Numerical simulation of pollutant dispersion was also conducted to calculate individual pollution exposure at bus stops. The results of PEMS tests showed no significant differences between bus emissions generated near two different types of stops. However, the effect of platform types on overall traffic emissions was revealed using traffic simulation. The results demonstrated that bus bays reduced the emissions of other heavy-duty vehicles. However, bus bays were not always effective during rush hours. The study also highlighted the importance of the location of bus stops, the number of bus lines, and the length of the platform, in addition to dynamic characteristics of traffic flows in the design of bus stop platforms. Bus stop platforms also affected individuals’ exposure due to the changes in the pollutant flow field. The passenger’s exposure at one bus stop was influenced by both the platform type and standing location. Results suggested that in a condition with a wind direction perpendicular to the bus stop shelter, the total exposure level to CO was lower at the bus bay stop if a passenger stood at the upstream of the station platform. However, the exposure was less at the downstream of the curbside bus stop.

A rational hybrid RANS-LES model for CFD predictions of microclimate and environmental quality in real urban structures

We report on the application and comparative assessment of two rational turbulence modelling approaches for the computer simulation of air flow and pollutant dispersion in real urban environment: a stand-alone unsteady Reynolds-averaged Navier-Stokes eddy-viscosity model (URANS), and its blend with Large-eddy simulations (LES) in a hybrid mode (HRL). The elliptic-relaxation (k−ε)ζ−feddy-viscosity model was applied in both methods. The models, verified earlier in a range of engineering flows including heat transfer, were here validated in two environmental benchmark cases, a single building and an idealized urban settlement, both subjected to a steady wind. The velocity field and pollutant concentration are better predicted by the HRL method in both benchmarks. The HRL is then applied to predictions of air flow and spreading of pollutant from road traffic in downtown of a real city (Sarajevo) containing 100 realistic buildings. The simulations were performed with the in-house open-source CFD code T-Flows, specifically optimized for a fast and efficient high-quality unstructured meshing of the terrain orography and building configurations. The benchmark validations demonstrated that, compared with the standard k−ε, in typical urban applications with complex urban shapes and arrangements the accuracy and credibility of the predictions can substantially be improved by applying a physically sounder and yet still relatively simple ζ−f eddy-viscosity model that specifically accounts for the elliptic inviscid wall-blocking effects and near-wall stress anisotropy. The benchmarking also showed that still further improvements are achieved by using the HRL scheme which ensures a rational balance in capturing the important physics and the computational economy.

Key emergency response technologies for abrupt air pollution accidents in China

Abrupt air pollution accidents can endanger people's health and destroy the local ecological environment. The appropriate emergency response can minimize the harmful effects of accidents and protect people's lives and property. This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years. With decades of effort, China has made significant progress in emergency monitoring technologies and equipment, source estimation technologies, pollutant dispersion simulation technologies and others. Many effective domestic emergency monitoring instruments (e.g., portable DOAS/FT-IR systems, portable FID/PID systems, portable GC-MS systems, scanning imaging remote sensing systems, and emergency monitoring vehicles) had been developed which can meet the demands for routine emergency response activities. A monitoring layout technique combining air dispersion simulation, fuzzy comprehensive evaluation, and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources. Multiple source estimation technologies, including the forward method and the inversion method, have been established and evaluated under various scenarios. Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed. A comprehensive emergency response platform integrating database support, source estimation, monitoring schemes, fast monitoring of pollutants, pollution predictions and risk assessment was developed based on the technical idea of "source identification - model simulation - environmental monitoring" dynamic interactive feedback. It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.

Numerical Analysis of the Atmospheric Boundary-Layer Turbulence Influence on Microscale Transport of Pollutant in an Idealized Urban Environment

The mesoscale atmospheric model Meso-NH is used to investigate the influence of mesoscale atmospheric turbulence on the mean flow, turbulence, and pollutant dispersion in an idealized urban-like environment, the array of containers investigated during the Mock Urban Setting Test field experiment. First, large-eddy simulations are performed as in typical computational fluid dynamics-like configurations, i.e., without accounting for the atmospheric- boundary-layer (ABL) turbulence on scales larger than the building scale. Second, in a multiscale configuration, turbulence of all scales prevailing in the ABL is accounted for by using the grid-nesting approach to downscale from the mesoscale to the microscale. The building-like obstacles are represented using the immersed boundary method and a new turbulence recycling method is used to enhance the turbulence transition between two nested domains. Upstream of the container array, flow characteristics such as wind speed, direction and turbulence kinetic energy are well reproduced with the multiscale configuration, showing the efficiency of the grid-nesting approach in combination with turbulence recycling for downscaling from the mesoscale to the microscale. Only the multiscale configuration is able to reproduce the mesoscale turbulent structures crossing the container array. The accuracy of the numerical results is evaluated for wind speed, wind direction, and pollutant concentration. The microscale numerical simulation of wind speed and pollutant dispersion in an urban-like environment benefits from taking into account the ABL turbulence. However, this benefit is significantly less important than that described in the literature for the Oklahoma City Joint Urban 2003 real case. The present study highlights that pollutant dispersion simulation improvement when accounting for ABL turbulence is dependent on the specific configuration of the city.

Large Eddy simulation of tracer gas dispersion in a cavity

This paper assesses the prediction of inert tracer gas dispersion within a cavity of height (H) 1.0 m, and unity aspect ratio, using large Eddy simulation (LES). The flow Reynolds number was 67 000, based on the freestream velocity and cavity height. The flow upstream of the cavity was laminar, producing a cavity shear layer which underwent a transition to turbulence over the cavity. Three distinct meshes are used, with grid spacings of (coarse), (intermediate), and (fine) respectively. The Smagorinsky, WALE, and Germano-Lilly subgrid-scale models are used on each grid to quantify the effects of subgrid-scale modelling on the simulated flow. Coarsening the grid led to small changes in the predicted velocity field, and to substantial over-prediction of the tracer gas concentration statistics. Quantitative metric analysis of the tracer gas statistics showed that the coarse grid simulations yielded results outside of acceptable tolerances, while the intermediate and fine grids produced acceptable output. Interrogation of the fluid dynamics present in each simulation showed that the evolution of the cavity shear layer is heavily influenced by the grid and subgrid scale model. On the coarse and intermediate grids the development of the shear layer is delayed, inhibiting the entrainment and mixing of the tracer gas into the shear layer, reducing the removal of the tracer gas from the cavity. On the fine grid, the shear layer developed more rapidly, resulting in enhanced removal of the tracer gas from the cavity. Concentration probability density functions showed that the fine grid simulations accurately predicted the range, and the most probable value, of the tracer gas concentration towards both walls of the cavity. The results presented in this paper show that the WALE and Germano-Lilly models may be advantageous over the standard Smagorinsky model for simulations of pollutant dispersion in the urban environment.

A review of research on vehicle exhaust dispersion model based on CFD simulation technology

CFD, comprising multiple types of softwares, involves complex technological theories and is used to solve profound issues with a huge amount of calculation. Given the complexity and profundity, this study selects Fluent, OpenFOAM and Star-CCM+ as representatives to review the application of the CFD simulation technology in the vehicle exhaust dispersion models. Fluent, a commercial CFD software, started relatively early and has so far been the most widely used in the field of motor vehicle exhaust dispersion research; OpenFOAM, is open source and has a large number of models and algorithms. Apart from supporting pure model research, OpenFOAM has broad application prospects in coupling with the mesoscale model WRF to improve the accuracy of pollutant dispersion simulation; Star-CCM+, less applied in the research field of vehicle exhaust dispersion, focuses more on vehicle air conditioning system, vehicle radiator, refueling, vehicle aerodynamic noise source simulation and other related fields. The research provides theoretical basis and scientific reference for the application of CFD in the field of urban block-scale air quality research. In the future, with the rapid development of computer technology and the introduction of new theories and intelligent algorithms, CFD technology is very likely to achieve new breakthroughs and continue to enjoy even wider application in the research of motor vehicle exhaust dispersion.