Pollutant Dispersion Research Articles

Analysis of pollutant diffusion characteristics with intersection angle of 45° in environmental open channel

Analysis of pollutant diffusion characteristics with intersection angle of 45° in environmental open channel

CALINE4 and AERMOD modelling for roadway vehicle-related air pollution: a recent review in India.

Modelling and prediction of air quality facilitates the drafting of efficient guidelines and, in turn, proper management of adversely affected areas. In order to depict the air pollutants in urban centres, this research analyses two modelling tools: AERMOD and CALINE4. Both technologies provide distinct capabilities in the modelling of air quality from vehicular and other emissions. CALINE4, a Gaussian dispersion model, specifies pollutant dispersion from mobile sources along roadways. It boasts a user-friendly interface and road-specific modelling capabilities, factoring in traffic speed and vehicle emissions. However, it simplifies intricate flow patterns and relies on primary meteorological data. On the other hand, AERMOD is a versatile model suitable for various emission sources, including both mobile and stationary sources. It excels at capturing diverse atmospheric processes but demands precise meteorological, terrain, and emission data. AERMOD is often preferred for regulatory compliance assessments, although it entails a steeper learning curve and higher computational requirements. The choice between CALINE4 and AERMOD hinges on study needs, data availability, and desired modelling precision. This review offers an overview to assist researchers in making informed model selections for assessing vehicle-related pollution, critical aspects of urban sustainability, and air quality management.

The Gaussian Plume Model Equation for Atmospheric Dispersion Corrected for Multiple Reflections at Parallel Boundaries: A Mathematical Rewriting of the Model and Some Numerical Testing

The well-known Gaussian plume model has proven to be very useful in simulating the atmospheric dispersion of air pollutants (both gaseous and particulates). Nevertheless, the nature of the model presents problems in the actual computation of concentrations when the plume is confined between two parallel boundaries due to the occurrence of multiple reflections. The ground and temperature inversion lid (especially, when the inversion layer is at low levels in the atmosphere) with a chimney stack releasing the effluent below the latter, is one contextual example of horizontal parallel reflecting boundaries. A second example is buildings confining a roadway on either side, with motor vehicles emitting pollution within the street canyon (or urban notch). In such cases, multiple reflections should be accounted for, otherwise the model underpredicts the resulting concentration. This paper presents a mathematical rewriting of the Gaussian plume model equation corrected for multiple reflections when the pollution source is confined between parallel boundaries. The obtained result is most appropriate when the parallel boundaries are rigid, and near-complete reflection is achieved, e.g., street canyon environment (second quoted example). It is worth noting that the relevant mathematical derivations and definitions are all included in the paper to facilitate reading and to ensure comprehensiveness in the presentation. Additionally, the outcome of some preliminary numerical testing is presented. The latter indicates that the new formulation is mathematically stable and yields interesting results. Further numerical investigation and experimental evaluation are merited.

Evaluating the effects of envelope features on the pollutant distribution and ventilation performance by CFD simulations and scaled outdoor experiments

Previous studies on the effects of envelope features on ventilation performance have neglected the buoyancy effect or simplified it as a uniform surface heating effect. However, envelope features can create a shading effect that changes the temperature distribution and enhances the buoyancy effect, thus resulting in inaccurate findings. We conducted computational fluid dynamics (CFD) simulations based on scaled outdoor experiments to investigate the effects of different envelope features (balconies, overhangs, and wing walls) on pollutant dispersion and ventilation performance. The buoyancy effect created a new local vortex and changed the wind flow pattern at the base of the flat-facade and wing wall street canyons. The age of the air at the base of the flat-facade, balcony, overhang, and wing wall street canyons increased by 30.23 %, 20.45 %, 21.74 %, and 30.95 %, respectively. Moreover, when investigating the effects of envelope features on ventilation performance while ignoring the buoyancy effect, there was a high error rate in the ventilation performance, and the rates were as follows: wing wall (24.03 %) > flat-facade (23.20 %) > overhang (18.56 %) > balcony (14.05 %). This study provides a suitable methodology for investigating the effects of different envelope features on pollutant dispersion and ventilation performance in two-dimensional street canyons.

Rapid prediction for the transient dispersion of leaked airborne pollutant in urban environment based on graph neural networks

Rapidly predicting airborne pollutant dispersion in urban is vital for ventilation design and evacuation planning. Computational fluid dynamics (CFD) simulations are commonly used to provide accurate predictions, but the computational cost is too high. Although graph neural networks (GNNs) provide fast predictions of flow fields by manipulating unstructured mesh on GPU, they suffer from high memory usage and accuracy decreases when applied to large-scale urban scenes. Moreover, it is difficult for GNNs to learn the coupled relationship between wind field and pollutant concentration field. We propose a multi-objective GNN model as CFD surrogate to rapidly predict the transient dispersion of airborne pollutant under the influence of complex wind field patterns in urban environment. Based on random urban layouts generated by a 2D bin packing algorithm, we employ a validated CFD model to construct a sample dataset of wind fields and concentration fields. We leverage graph pooling and multi-scale feature fusion to improve prediction accuracy, and subgraph partitioning of both wind field and concentration field to reduce GPU memory usage. The results show that our GNN model at its best runs 1–2 orders of magnitude faster than CFD simulation with accuracy evaluation metrics R2=0.92, and achieves 70 % GPU memory reduction.

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.

Pollutant cross-transmission in courtyard buildings: Wind tunnel experiments and computational fluid dynamics (CFD) evaluation

Courtyards, a historical architectural feature surrounded by buildings, are common in urban housing and residential complexes. These spaces, often open-air and with rooms facing them, are crucial for daylight and natural ventilation. While courtyards are essential for introducing fresh airflow into adjacent indoor areas, the effectiveness of natural ventilation may be compromised due to potentially poor air circulation from limited openings. This raises a significant concern: could the design of courtyards inadvertently facilitate pollutant cross-transmission? Despite a wealth of research focused on airflow within courtyards, the indoor spaces in proximity to these courtyards have often been neglected in previous works, particularly concerning the exchange of pollutants between the indoor and courtyard environment. This research investigates the dynamics of indoor-outdoor pollutant cross-transmission in courtyard buildings, assessing factors like external wind flow patterns and internal pollutant sources. Wind tunnel experiments were conducted to measure internal pressure and CO2 concentration and to validate a computational model of the courtyard with 12 rooms. The validated Computational Fluid Dynamics (CFD) models were used to simulate the dispersion of pollutants from internal rooms under different wind conditions. The results showed that the k-epsilon Realizable model accurately simulated internal surface pressure distribution and pollutant dispersion in the courtyard building. It was observed that when pollutants were released from the downwind east-facing ground floor room, CO2 concentrations in adjacent side rooms on the same floor were significantly higher, increasing from the baseline of 400 ppm and reaching up to 3211 ppm in the north-facing room at a wind speed of 4.51 m/s and wind direction of 0°. Conversely, when pollutants originated from north- and south-facing side rooms, pollutants were minimally dispersed to adjacent rooms. Furthermore, at a wind direction of 45°, pollutants from wind-exposed rooms predominantly dispersed to downwind rooms, with peak concentrations exceeding 2400 ppm in downwind rooms. These findings demonstrate that pollutant dispersion is highly dependent on wind direction and the location of the pollutant source. The study concludes that while courtyards enhance indoor environmental quality through natural ventilation, their design must be carefully considered to prevent unintended pollutant cross-transmission, particularly under varying wind conditions and pollutant source locations.

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

A long-term Doppler wind LiDAR study of heavy pollution episodes in western Yangtze River Delta region, China

Previous studies are primarily based on surface air pollution for a single event, leaving research on the temporal characteristics of aerosols and wind fields in the atmospheric boundary layer (ABL) and their associations unclear due to a lack of long-term vertical profile data. This study was the first to conduct long-term Doppler wind LiDAR measurements from Sep. 2019 to Aug. 2022 in Hefei in western Yangtze River Delta (YRD) region, China. The spatiotemporal characteristics of retrieved aerosol backscatter coefficient (β) and wind profiles were analyzed from the perspective of long-term statistics and typical heavy pollution episodes (HPEs). The seasonal profile of β showed a peak in the near-surface layer meanwhile the overall β profile (<0.5 km) was the highest in winter but lowest in summer. Combined with ground-based meteorological and air quality observations, 12 HPEs were identified and classified into dust-related events and fog-haze episodes. The results showed a consistency between hourly variations in PM10 (particulate matter smaller than 10 μm) concentration and β retrieved at 300 m during a high PM10 concentration (>150 μg/m3) period. Different roles of horizontal wind at different altitudes and its associated time delay effect on surface PM10 pollution were evaluated based on correlation coefficients (Ф) and air pollution diffusion conditions. Significant positive Ф values were noticed below 0.5 km during the entire dust-related EP4 and EP6, indicating that the higher wind speeds could exacerbate PM10 pollution. In contrast, large negative Ф values meant the removal of PM10 pollutants by strong winds below 0.8 km during 24 h after peak in EP3. Combining with backward trajectory analysis and meteorological condition, notable transboundary pollution with positive contributions from upper winds (>1.5 km) was discovered in dust-related EP1, EP4, EP7, EP9, and EP10. Time delay effect (1-h/2-h lag) of upper winds (>0.8 km) on surface PM10 pollution was explored in EP5, EP6, EP7, EP8, and EP9. In spring dust-related HPEs, surface PM10 pollution was mostly contributed by long-range transport of aerosol particles at higher altitudes (>1.5 km) from the northwest direction, driven by the Mongolian cyclone and the cold front system. Transboundary aerosols originated from the northern part of Anhui province and the YRD region in the middle altitudes (∼0.5 km) was the main contributor to fog-haze HPEs. The findings demonstrated the ability of the real-time Doppler wind LiDAR system to monitor transboundary air pollution and provided a scientific reference for policy makers.

Spatial and temporal changes of air quality in Shandong Province from 2016 to 2022 and model prediction

This study investigates the spatial and temporal dynamics of air quality in Shandong Province from 2016 to 2022. The Air Quality Index (AQI) showed a seasonal pattern, with higher values in winter due to temperature inversions and heating emissions, and lower values in summer aided by favorable dispersion conditions. The AQI improved significantly, decreasing by approximately 39.4 % from 6.44 to 3.90. Coastal cities exhibited better air quality than inland areas, influenced by industrial activities and geographical features. For instance, Zibo's geography restricts pollutant dispersion, resulting in poor air quality. CO levels remained stable, while O3 increased seasonally due to photochemical reactions in summer, with correlation coefficients indicating a strong positive correlation with temperature (r = 0.65). Winter saw elevated NO2 levels linked to heating and vehicular emissions, with an observed increase in correlation with AQI (r = 0.78). PM2.5 and PM10 concentrations were higher in colder months due to heating and atmospheric dust, showing a significant decrease of 45 % and 40 %, respectively, over the study period. Predictive modeling forecasts continued air quality improvements, contingent on sustained policy enforcement and technological advancements. This approach provides a comprehensive framework for future air quality management and improvement.

Optimization of wheel brow structures of a van considering rainwater pollutants based on discrete phase model

Four optimization models were proposed to reduce the impact of pollutants from vans on themselves and surrounding vehicles. The adsorption of pollutants on the body of the van in rainy conditions and the diffusion of pollutants into the external environment were numerically investigated using the Discrete Phase Model (DPM) for vans having different wheel brow structures. The pressure distribution on the surface of the van, the surrounding flow field, and the raindrop distributions of various external positions on and around the van were analyzed and compared. The results indicated that the van with externally covered wheel brow model was most effective in inhibiting the diffusion of rainwater pollutants from the van under rainy conditions. Compared with the original model, the reduction in the polluted area was 11.19%, the reduction in the influence of the visual field on the rear vehicle was 25.4%, and the reduction in the diffusion of pollutants on the bodies of the side vehicle was 20.7%.

Study of pollutant transport under linear sorption in a groundwater reservoir

Abstract Pollutant dispersion in a porous medium can be modelled mathematically to forecast its concentration distribution profile. The governing equation of pollutant transport is modelled as a partial differential equation. Effects of sorption, zero-order production rate and first-order decay rate on pollutant transport are incorporated in the present study. The temporarily dependent pulse-type input source decaying exponentially is assumed at the origin of the domain. The solution of the proposed transport equation is derived by Laplace transform method for the respective time split domain. Matlab algorithm is developed to illustrate the obtained analytical solutions graphically for various hydrological input data. The pollutant distribution profiles in the medium are obtained for different times and porosities. The pollutant transport nature is examined for various forms of velocity flow pattern in presence and absence of input source. Also, the derived solution is compared graphically under special case with the existing solution and found the results with good agreement.

Green Lane Planning for Safety, Beauty, and Reduction of the Diffusion of Air Pollutants to the Environment in the Boyolali Interchange on Semarang-Solo Toll Road

Abstract The high mobility of people requires fast transportation making toll roads as an alternative route to break up congestion and shorten the distance to a place. The availability of toll roads that are passed by many motorized vehicles, causes air pollution. To reduce the impact of air pollution, greenery is needed that can absorb exhaust emissions. In this study, motor vehicle exhaust emissions focus on NO2 gas. The purpose of this study was to analyze the emission of NO2 gas pollutants from motor vehicles, the absorption capacity of NO2 by vegetation, and to plan green lane that can improve the quality of the interchange landscape. The research was conducted at the Boyolali Interchange. The research method used is descriptive-quantitative based on the potential and constraints on the site, as well as analysis of emissions and vegetation that can absorb NO2 gas pollutants. Based on the results of the analysis, the development of green lane space is divided based on the function of vegetation which includes clear zone, cushion planting, aesthetics, identity, conservation, and guides which it supported with trees, and shrubs. The area of land that has the potential to be developed into green lane is 41,956.3 m2. The volume of vehicles is 66,637 per day with the resulting NO2 gas emission of 57.797 g. After planning, the emission that can be absorbed by plants is 48,293.50 g. Planned green lane of the Boyolali Interchange can reduce 83,56% of NO2 gas emissions released by motorized vehicles.

A simple model for predicting the hydraulic conductivity of MICP-treated sand.

In this research paper, we introduce a novel and sustainable approach for forecasting the hydraulic conductivity of sand layers subjected to microbial-induced carbonate precipitation (MICP) to mitigate the diffusion of toxic pollutants. The proposed model uniquely integrates the impact of varying CaCO3 contents on the void ratio and estimates the average particle size of CaCO3 crystals through scanning electron microscopy (SEM) analysis. By incorporating these parameters into the K-C equation, a simplified predictive model is formulated for assessing the hydraulic conductivity of MICP-treated sand layers. The model's effectiveness is validated through comparison with experimental data and alternative models. The outcomes demonstrate a substantial reduction in hydraulic conductivity, with a decrease ranging between 93 and 97% in the initial assessment and a decrease between 67 and 92% in the follow-up assessment, both at 10% CaCO3 content. Notably, the hydraulic conductivity shows an initial sharp decrease followed by stabilization. These findings provide valuable insights into improving the prediction of hydraulic conductivity in MICP-treated sand layers, promoting a sustainable method for preventing pollution dispersion.

Interior three-dimensional acoustic modeling and modal analysis using wavelet-based finite-element approach.

This paper introduces two-dimensional (2D) and 3D acoustic modeling and modal analysis using the wavelet finite-element method (WFEM). Governed by the Helmholtz equation, the acoustic domain is parameterized and analyzed using the scaling functions of B-spline wavelets, which facilitates the construction of elements with varying numbers of nodes via multi-resolution analysis. The wavelet-based shape functions provide a semi-orthogonal basis that enables rapid searching for approximate solutions in Lebesgue spaces, thereby offering significantly reduced interpolation errors and computational burden. Numerical examples are considered using WFEM, comprising a 2D acoustic problem involving a tube for predicting acoustic pressure and eigenfrequency investigations, and 3D acoustic problems involving a cubic room and an L-shaped room for capturing acoustic characteristics. The results are compared with those of (i) standard FEM with the same mesh and (ii) analytical solutions. Importantly, WFEM demonstrates stability by being insensitive to internal mesh size variations, indicating that B-spline wavelet elements have minimal effects on the numerical results. Furthermore, B-spline wavelet elements effectively control the pollution (dispersion) error of numerical methods when imposing Neumann boundary conditions in the high-frequency range, and they reduce interpolation errors caused by polynomial interpolation in the low-frequency domain.

Pick the butt up! Upcycling cigarette butts in road building material for sustainable road construction.

Abstract Roads are the lifeline of any nation. They are vital in passenger and freight transportation. Over usage and heavy loads put a lot of stress and strain on the health of the roads. On the other hand, cigarette butts (CB) are discarded unsafely after smoking and persist in nature as the cellulose acetate content in them, which is a microplastic, that does not decompose easily leading to a lot of littering, pollution and toxin dispersal in the environment. This proposed research utilizes the discarded cigarette butts into road construction material increasing its strength, durability and resistance against rutting while reducing costs and thermal conductivity to maintaining better surface temperatures. The utilization of discarded cigarette butts in road construction is a sustainable solution to not only strengthen the roads, but also reduce the negative environmental impact of improper cigarette butt disposal. In contrast to conventional bitumen roads, these roads possess superior toughness along with broad level durability. Multi-pronged approach to research was implemented here that included firstly a thorough literature review, conceiving the research design, conduct of research steps, evaluation of experimental results, and finally drawing conclusions from them. These experiments included retrieval of cellulose acetate from CBs, traditional physical and rheology tests, sieve analysis by Rothfuch’s technique and Marshall stability test. This paper aims to contribute to sustainable development goals by utilizing CBs to strengthen roads and clean the environment by eliminating this litter.

Effectiveness of inter-regional collaborative emission reduction for ozone mitigation under local-dominated and transport-affected synoptic patterns.

In recent years, the concentrations of ozone and the pollution days with ozone as the primary pollutant have been increasing year by year. The sources of regional ozone mainly depend on local photochemical formation and transboundary transport. The latter is influenced by different weather circulations. How to effectively reduce the inter-regional emission to control ozone pollution under different atmospheric circulation is rarely reported. In this study, we classify the atmospheric circulation of ozone pollution days from 2014 to 2019 over Central China based on the Lamb-Jenkinson method and the global analysis data of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5) operation. The effectiveness of emission control to alleviate ozone pollution under different atmospheric circulation is simulated by the WRF-Chem model. Among the 26 types of circulation patterns, 9 types of pollution days account for 79.5% of the total pollution days and further classified into 5 types. The local types (A and C type) are characterized by low surface wind speed and stable weather conditions over Central China due to a high-pressure system or a southwest vortex low-pressure system, blocking the diffusion of pollutants. Sensitivity simulations of A-type show that this heavy pollution process is mainly contributed by local emission sources. Removing the anthropogenic emission of pollutants over Central China would reduce the ozone concentration by 39.1%. The other three circulation patterns show pollution of transport characteristics affected by easterly, northerly, or southerly winds (N-EC, EC, S-EC-type). Under the EC-type, removing anthropogenic pollutants of East China would reduce the ozone concentration by 22.7% in Central China.

A modeling framework to assess fenceline monitoring and self-reported upset emissions of benzene from multiple oil refineries in Texas

Benzene as one type of hazardous air pollutants (HAPs) is produced by industrial production processes and/or emitted during upset events caused by man-made or natural accidents. Although upset emissions of benzene can be a significant contributor to the total emission, it is still challenging to quantify. This study first develops a fast modeling framework using obstacle-resolving computational fluid dynamics modeling to compare the modeled within-facility-scale passive pollutant dispersion with the observed levels based on self-reported emissions for fourteen facilities in Texas, United States. Results of numerical simulations demonstrate that neglecting the obstacle effect can underpredict (overpredict) the near-(far-)field concentrations for a low source. For a source located above obstacles, underprediction occurs at all distances. The diagnostic framework is applied to 107 self-reported upset emission events for fourteen petroleum refineries in Texas from year 2019–2022. Considering different metrics across all events, it can be concluded that the modeled concentrations based on self-reported emissions likely underpredict the observed concentration increments. Depending on the possible source height, the median factor of underprediction ranges from 3 to 95 based on the average-plume metric. The agreement between model and observation is better for events characterized by high emission amounts and rates, which also correspond to high observed concentration increments. Overall, the research highlights the importance of considering obstacles and demonstrates the potential application of the current approach as an efficient diagnostic method for self-reported upset emissions using fenceline observations of HAPs.

Simulation and Analysis of Oil Pollutant Diffusion in River Affected by Coking Wash Oil Contaminated Groundwater

Simulation and Analysis of Oil Pollutant Diffusion in River Affected by Coking Wash Oil Contaminated Groundwater

Fast flow field prediction of pollutant leakage diffusion based on deep learning.

Predicting pollutant leakage and diffusion processes is crucial for ensuring people's safety. While the deep learning method offers high simulation efficiency and superior generalization, there is currently a lack of research on predicting pollutant leakage and diffusion flow field using deep learning. Therefore, it is necessary to conduct further studies in this area. This paper introduces a two-level network method to model the flow characteristics of pollutant diffusion. The proposed method in this study demonstrates a significant enhancement in flow field prediction accuracy compared to traditional deep learning methods. Moreover, it improves computational efficiency by over 800 times compared to traditional computational fluid dynamics (CFD) methods. Unlike conventional CFD methods that require grid expansion to calculate all operation conditions, the deep learning method is not confined by grid limitations. While deep learning methods may not entirely replace CFD methods, they can serve as a valuable supplementary tool, expanding the versatility of CFD methods. The findings of this research establish a robust foundation for incorporating deep learning methods in addressing pollutant leakage and diffusion challenges.