On the use of numerical modelling for near-field pollutant dispersion in urban environments--A review

Assessing the impact of mining on cyclic and linear methylsiloxane distribution in Tibetan soils: Source contribution and transport pattern

The pervasive presence of methylsiloxanes (MSs), comprising linear and cyclic congeners, in the environment poses significant ecological risks, yet the understanding of their transport mechanisms and deposition patterns remains limited. This study analyzed the concentrations of 12 linear-MSs (L3-L14) and 7 cyclic-MSs (D3-D9) in 29 surface soil samples collected across varying altitudes (3726 to 4863 m) near the Jiama mining sector in Tibet, aiming to investigate the distribution and transport dynamics of MSs from the emission source. The distribution of total MS concentration (ranging from 50.1 to 593 ng/g) showed a remarkable correlation with proximity to the mining site, suggesting the emergent source of mining activities for the MSs in the remote environment of the Tibetan Plateau. Employing the innovative model of robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), the analysis predicted that the mining operations contributing 57.1 % of the total soil MSs, would significantly surpass contributions from traffic emissions (14.7 %), residential activities (13.2 %), and the environmental factor of total organic matter content (14.9 %). The Boltzmann equation effectively modeled the distribution pattern of soil MSs, highlighting atmospheric transport and gravitational settling as key distribution mechanisms. However, linear-MSs exhibited longer transport distances than cyclic-MSs and were more profoundly affected by prevailing wind directions, suggesting their differential environmental behaviors and risks. Our study underscored that the mining sector possibly emerged as a significant source of Tibetan MSs, and provided insights into the transport and fate of MSs in remote, high-altitude environments. The findings emphasize the need for targeted pollution control strategies to mitigate the environmental footprint of mining activities in Tibet and similar regions.

Air pollution and climate change as grand challenges to sustainability

There is a cross-disciplinary link between air pollution, climate crisis, and sustainable lifestyle as they are the most complex struggles of the present century. This review takes an in-depth look at this relationship, considering carbon dioxide emissions primarily from the burning of fossil fuels as the main contributor to global warming and focusing on primary SLCPs such as methane and ground-level ozone. Such pollutants severely alter the climate through the generation of greenhouse gases. The discussion is extensive and includes best practices from conventional pollution control technologies to hi-tech alternatives, including electric vehicles, the use of renewables, and green decentralized solutions. It also addresses policy matters, such as imposing stricter emissions standards, setting stronger environmental regulations, and rethinking some economic measures. Besides that, new developments such as congestion charges, air ionization, solar-assisted cleaning systems, and photocatalytic materials are among the products discussed. These strategies differ in relation to the local conditions and therefore exhibit a varying effectiveness level, but they remain evident as a tool of pollution deterrence. This stresses the importance of holistic and inclusive approach in terms of engineering, policies, stakeholders, and ecological spheres to tackle.

Numerical Analysis of Indoor Air Characteristics and Window Screen Influence on Particulate Matter Dispersion in a Childcare Center Using Computational Fluid Dynamics

Indoor exposure to outdoor pollutants adversely affects health, varying with building dimensions and particularly ventilation that have critical role on their indoor dispersion. This study assesses the impact of outdoor air on indoor air quality in a child care center. Computational fluid dynamics was utilized to analyze the dispersion of particulate matter, with a specific focus on window screens featuring 6 distinct pore sizes ranging from 0.8 mm to 2 mm and 2 different thicknesses of 0.5 mm and 0.1 mm. Results indicate that the presence of a window screen offers significant advantages in controlling particle infiltration compared to scenarios without a screen, as larger particles tend to pass directly through the window within the breathing zone. The scenario without window screens minimizes pressure drop but lacks enhanced particle capture capabilities. However, for effective particle reduction, the window screen with a pore size of 0.8 mm (R0.8T2) and a thickness of 0.5 mm proves to be the most beneficial, achieving the particle filtering efficiency of approximately 54.16%, while the larger window screen with a pore size of 2 mm and a thickness of 1 mm exhibits the lowest efficiency at about 23.85%. Nonetheless, screens with very small sizes are associated with a high-pressure drop, impacting energy efficiency, and overall window performance. Larger pores with smaller thicknesses (0.5 mm) reduced particle count by approximately 45.97%. Therefore, the significance of window screen thickness beyond pore size for particle reduction efficiency is highlighted, emphasizing screens' role in indoor air quality and health protection.

Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use

CO2 monitoring is important for carbon emission evaluation. Low-cost and medium-precision sensors (LCSs) have become an exploratory direction for CO2 observation under complex emission conditions in cities. Here, we used a calibration method that improved the accuracy of SenseAir K30 CO2 sensors from ±30 ppm to 0.7-4.0 ppm for a CO2-monitoring instrument named the SENSE-IAP, which has been used in several cities, such as in Beijing, Jinan, Fuzhou, Hangzhou, and Wuhan, in China since 2017. We conducted monthly to yearly synchronous observations using the SENSE-IAP along with reference instruments (Picarro) and standard gas to evaluate the performance of the LCSs for indoor use with relatively stable environments. The results show that the precision and accuracy of the SENSE-IAP compared to the standard gases were rather good in relatively stable indoor environments, with the short-term (daily scale) biases ranging from -0.9 to 0.2 ppm, the root mean square errors (RMSE) ranging from 0.7 to 1.6 ppm, the long-term (monthly scale) bias ranging from -1.6 to 0.5 ppm, and the RMSE ranging from 1.3 to 3.2 ppm. The accuracy of the synchronous observations with Picarro was in the same magnitude, with an RMSE of 2.0-3.0 ppm. According to our evaluation, standard instruments or reliable standard gases can be used as a reference to improve the accuracy of the SENSE-IAP. If calibrated daily using standard gases, the bias of the SENSE-IAP can be maintained within 1.0 ppm. If the standard gases are hard to access frequently, we recommend a calibration frequency of at least three months to maintain an accuracy within 3 ppm.

Volatile organic compounds (VOCs) emissions from internal floating-roof tank in oil depots in Beijing: Influencing factors and emission reduction strategies analysis

The internal floating-roof tank is the main type of storage tank for refined oil products. The volatile organic compounds (VOCs) emission from the internal floating-roof tank plays a dominant role in the unorganized emission source of the oil depot. In this study, we selected six typical oil depots in Beijing to investigate VOC emission characteristics from the tank top vent hole using infrared imaging technology and flame ionization detector (FID). The results reveal that infrared thermal imager is efficient in quickly identifying the emission level of the tank discharge point. The ambient temperature and wind speed have a direct effect on sealing loss, the turnover can greatly influence the wall hanging loss, and the concentration of VOCs emitted from the tank top vent hole is negatively correlated with liquid height. Furthermore, the influence of accessories type of the internal floating-roof tank on the concentration of VOCs emission from the top vent hole is also studied when other parameters remain unchanged, and find the floating deck type and sealing mode have a significant influence on their VOCs emissions, of which the combination of pontoon type floating deck and secondary seal are effective in controlling the concentration of VOCs emitted from the tank top vent hole. Finally, based on our experimental results, several feasible emission reduction strategies are proposed in terms of source prevention and process control in order to achieve the fine management of the whole process. This paper provides important technical support and policy thoughts for VOCs emission control during oil storage.

Reassessing the role of urban green space in air pollution control

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity

BACKGROUND

Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question.

OBJECTIVE

The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales.

DISCUSSION

The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

Simulating Microscale Urban Airflow and Pollutant Distributions Based on Computational Fluid Dynamics Model: A Review

Urban surfaces exert profound influences on local wind patterns, turbulence dynamics, and the dispersion of air pollutants, underscoring the critical need for a thorough understanding of these processes in the realms of urban planning, design, construction, and air quality management. The advent of advanced computational capabilities has propelled the computational fluid dynamics model (CFD) into becoming a mature and widely adopted tool to investigate microscale meteorological phenomena in urban settings. This review provides a comprehensive overview of the current state of CFD-based microscale meteorological simulations, offering insights into their applications, influential factors, and challenges. Significant variables such as the aspect ratio of street canyons, building geometries, ambient wind directions, atmospheric boundary layer stabilities, and street tree configurations play crucial roles in influencing microscale physical processes and the dispersion of air pollutants. The integration of CFD with mesoscale meteorological models and cutting-edge machine learning techniques empowers high-resolution, precise simulations of urban meteorology, establishing a robust scientific basis for sustainable urban development, the mitigation of air pollution, and emergency response planning for hazardous substances. Nonetheless, the broader application of CFD in this domain introduces challenges in grid optimization, enhancing integration with mesoscale models, addressing data limitations, and simulating diverse weather conditions.

Empirical mode decomposition of the atmospheric flows and pollutant transport over real urban morphology

The momentum transport and pollutant dispersion in the atmospheric surface layer (ASL) are governed by a broad spectrum of turbulence structures. Whereas, their contributions have not been explicitly investigated in the context of real urban morphology. This paper aims to elucidate the contributions from different types of eddies in the ASL over a dense city to provide the reference of urban planning, realizing more favorable ventilation and pollutant dispersion. The building-resolved large-eddy simulation dataset of winds and pollutants over the Kowloon downtown, Hong Kong, is decomposed into a few intrinsic mode functions (IMFs) via empirical mode decomposition (EMD). EMD is a data-driven algorithm that has been successfully implemented in many research fields. The results show that four IMFs are generally enough to capture most of the turbulence structures in real urban ASL. In particular, the first two IMFs, which are initiated by individual buildings, capture the small-scale vortex packets that populate within the irregular building clusters. On the other hand, the third and fourth IMFs capture the large-scale motions (LSMs) detached to the ground surface that are highly efficient in transport. They collectively contribute to nearly 40% of vertical momentum transport even with relatively low vertical turbulence kinetic energy (TKE). LSMs are long, streaky structures that mainly consist of streamwise TKE components. It is found that the open areas and regular streets promote the portion of streamwise TKE in LSMs, improving the vertical momentum transport and pollutant dispersion. In addition, these streaky LSMs are found to play a crucial role in pollutant dilution in the near field after the pollutant source, while the small-scale vortex packets are more efficient in transport in the mid-field and far-field.

Influence of spatial distribution pattern of buildings on the distribution of urban gaseous pollutants

Buildings are the main component of urban, and their three-dimensional spatial patterns affect meteorological conditions and consequently, the spatial distribution of gaseous pollutants (CO, NO, NO₂, and SO₂). This study uses the Jinan Central District as the study area and constructs a building spatial distribution index system based on DEM, urban road network, and building big data. ANOVA and spatial regression models were used to study the effects of building spatial distribution indicators on the distribution of gaseous pollutants along with their spatial heterogeneity. The results showed that (1) the effects of most of spatial distribution indexes of building on the concentration distribution of the four gaseous pollutants were significant, with one-way ANOVA outcomes reaching a significance level of 0.01 or more. The DEM mean, building altitude, and their interaction with other building spatial distribution indicators are important factors affecting the distribution of gaseous pollutants; The interaction of other three-factor indicators did not have a significant effect on the distribution of gaseous pollutant concentrations. (2) The spatial distribution of CO and NO₂ is mainly influenced by the indicators of the spatial distribution of buildings in this study unit, and the effects of CO and NO₂ concentrations in adjacent study units are the result of the action of stochastic factors. The NO and SO₂ concentrations are influenced by the spatial distribution index of buildings in this study unit, the neighborhood homogeneity index, and NO and SO2 concentrations. (3) Spatial heterogeneity was observed in the effects of building spatial distribution indicators on the concentrations of different pollutants. The GWR models constructed using CO and NO concentrations and building spatial distribution indicators were well fitted globally and locally. The CO and NO concentrations were negatively correlated with the mean topographic elevation and NO concentrations were correlated with building density.

Heat Wave and Bushfire Meteorology in New South Wales, Australia: Air Quality and Health Impacts

The depletion of air quality is a major problem that is faced around the globe. In Australia, the pollutants emitted by bushfires play an important role in making the air polluted. These pollutants in the air result in many adverse impacts on the environment. This paper analysed the air pollution from the bushfires from November 2019 to July 2020 and identified how it affects the human respiratory system. The bush fires burnt over 13 million hectares, destroying over 2400 buildings. While these immediate effects were devastating, the long-term effects were just as devastating, with air pollution causing thousands of people to be admitted to hospitals and emergency departments because of respiratory complications. The pollutant that caused most of the health effects throughout Australia was Particulate Matter (PM) PM_2.5 and PM₁₀. Data collection and analysis were covered in this paper to illustrate where and when PM_2.5 and PM_10, and other pollutants were at their most concerning levels. Susceptible areas were identified by analysing environmental factors such as temperature and wind speed. The study identified how these pollutants in the air vary from region to region in the same time interval. This study also focused on how these pollutant distributions vary according to the temperature, which helps to determine the relationship between the heatwave and air quality. A computational model for PM_2.5 aerosol transport to the realistic airways was also developed to understand the bushfire exhaust aerosol transport and deposition in airways. This study would improve the knowledge of the heat wave and bushfire meteorology and corresponding respiratory health impacts.

Performance Evaluation of the RANS Models in Predicting the Pollutant Concentration Field within a Compact Urban Setting: Effects of the Source Location and Turbulent Schmidt Number

Computational Fluid Dynamics (CFD) is used to accurately model and predict the dispersion of a passive scalar in the atmospheric wind flow field within an urban setting. The Mock Urban Setting Tests (MUST) experiment was recreated in this work to test and evaluate various modeling settings and to form a framework for reliable representation of dispersion flow in compact urban geometries. Four case studies with distinct source locations and configurations are modeled using Reynolds-Averaged Navier–Stokes (RANS) equations with ANSYS CFX. The performance of three widely suggested closure models of standard k−ε, RNG k−ε, and SST k−ω is assessed by calculating and interpreting the statistical performance metrics with a specific emphasis on the effects of the source locations. This work demonstrates that the overprediction of the turbulent kinetic energy by the standard k−ε counteracts the general underpredictions by RANS in geometries with building complexes. As a result, the superiority of the standard k−ε in predicting the scalar concentration field over the two other closures in all four cases is observed, with SST k−ω showing the most discrepancies with the field measurements. Additionally, a sensitivity study is also conducted to find the optimum turbulent Schmidt number (Sct) using two approaches of the constant and locally variable values.

Forecasting Fine-Grained Air Quality for Locations without Monitoring Stations Based on a Hybrid Predictor with Spatial-Temporal Attention Based Network

Air pollution in cities is a severe and worrying problem because it causes threats to economic development and health. Furthermore, with the development of industry and technology, rapid population growth, and the massive expansion of cities, the total amount of pollution emissions continue to increase. Hence, observing and predicting the air quality index (AQI), which measures fatal pollutants to humans, has become more and more critical in recent years. However, there are insufficient air quality monitoring stations for AQI observation because the construction and maintenance costs are too high. In addition, finding an available and suitable place for monitoring stations in cities with high population density is difficult. This study proposes a spatial-temporal model to predict the long-term AQI in a city without monitoring stations. Our model calculates the spatial-temporal correlation between station and region using an attention mechanism and leverages the distance information between all existing monitoring stations and target regions to enhance the effectiveness of the attention structure. Furthermore, we design a hybrid predictor that can effectively combine the time-dependent and time-independent predictors using the dynamic weighted sum. Finally, the experimental results show that the proposed model outperforms all the baseline models. In addition, the ablation study confirms the effectiveness of the proposed structures.

Dispersion Simulations of Radon Discharges between Neighboring Buildings and Their Sensitivity to Meteorology, Discharge Rate, and Building Geometry

ABSTRACT

In northern climates, it is common to install the discharges of radon sub-slab depressurization systems near ground level. However, this also elevates the ground level outdoor radon concentrations and raises the possibility of radon re-entrainment into homes. The study aims to assess outdoor radon concentrations near above-ground-level discharges along the surfaces of an emitting building and its close neighbor and identify parameters that most influence the dilution. This study employs a series of computational fluid dynamics calculations to assess concentrations along the exhaust-facing and non-exhaust-facing surfaces of the buildings. Different meteorological, venting, and building geometry parameters are explored. Boundary conditions for the CFD calculations are based on field measurements of the ground-level wind speeds and seasonal air temperatures and atmospheric stabilities. Outdoor concentrations can be as high as 7% of the discharge gas, although these become smaller at greater distances from the vent. The direction of the prevailing wind is a particularly important parameter, as it influences the formation of circulating building cavities and building wakes where radon could accumulate. The wind speed, atmospheric stability, and season (plume buoyancy) also have important influences on the outdoor radon concentrations, as do the velocity of the vent system and the size of the buildings. The study has assessed the dilution of the radon-laden exhaust gas and determined the outdoor concentrations that can be expected under a variety of conditions. These results can be used to inform regulators about the potential for radon re-entrainment into homes.

Release of phthalate esters from a local landfill in the Tibetan Plateau: Importance of soil particle-size specific association

High loads of phthalate esters (PAEs) in background regions can be directly attributed to the local sources, and their association with soil particles may determine the environment behaviors. However, little is known about the particle-size specific distributions of PAEs in soils from point source to the surroundings. In this study, 12 PAE congeners were measured in clay (< 2 μm), silt (2-63 μm) and sand fractions (63-250 μm) from surficial soils and soil profiles (0-200 cm) around the Lhasa landfill. The total concentrations of PAEs in bulk soils varied from 0.44 to 22.3 μg/g, with a dominance of bis(2-ethylhexyl) phthalate (DEHP). The clay-sorbed PAEs exhibited a decreasing trend with the increasing distance from landfill. This distribution pattern was well described by the Gaussian air pollution model, suggesting the airborne particles/gaseous transport of clay-sorbed PAEs. The Boltzmann equation explained the spatial variation of silt-sorbed PAEs, reflecting the atmospheric dispersion of silt-sorbed PAEs. In comparison, the sand-sorbed PAEs in surrounding soils showed downslope accumulation possibly due to the aeolian transport of sand particles. Half-life of the most abundant PAE congener DEHP was assumed based on the soil inventories from observed concentration and the Level III fugacity model simulations, and the results indicated significant longer half-life of DEHP in deeper soils (~24,000 h) than in surficial soils (5500 h). This study elucidates that the distribution and fate of soil PAEs would depend on their association with particles in the source area, and the relative stability of DEHP in deeper soils would further increase PAE inventory in soil compartment.

A Novel Method for Source Tracking of Chemical Gas Leakage: Outlier Mutation Optimization Algorithm

Chemical industrial parks, which act as critical infrastructures in many cities, need to be responsive to chemical gas leakage accidents. Once a chemical gas leakage accident occurs, risks of poisoning, fire, and explosion will follow. In order to meet the primary emergency response demands in chemical gas leakage accidents, source tracking technology of chemical gas leakage has been proposed and evolved. This paper proposes a novel method, Outlier Mutation Optimization (OMO) algorithm, aimed to quickly and accurately track the source of chemical gas leakage. The OMO algorithm introduces a random walk exploration mode and, based on Swarm Intelligence (SI), increases the probability of individual mutation. Compared with other optimization algorithms, the OMO algorithm has the advantages of a wider exploration range and more convergence modes. In the algorithm test session, a series of chemical gas leakage accident application examples with random parameters are first assumed based on the Gaussian plume model; next, the qualitative experiments and analysis of the OMO algorithm are conducted, based on the application example. The test results show that the OMO algorithm with default parameters has superior comprehensive performance, including the extremely high average calculation accuracy: the optimal value, which represents the error between the final objective function value obtained by the optimization algorithm and the ideal value, reaches 2.464e-15 when the number of sensors is 16; 2.356e-13 when the number of sensors is 9; and 5.694e-23 when the number of sensors is 4. There is a satisfactory calculation time: 12.743 s/50 times when the number of sensors is 16; 10.304 s/50 times when the number of sensors is 9; and 8.644 s/50 times when the number of sensors is 4. The analysis of the OMO algorithm's characteristic parameters proves the flexibility and robustness of this method. In addition, compared with other algorithms, the OMO algorithm can obtain an excellent leakage source tracing result in the application examples of 16, 9 and 4 sensors, and the accuracy exceeds the direct search algorithm, evolutionary algorithm, and other swarm intelligence algorithms.

How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne particles from a public health perspective - with implications for urban planning

Air pollution causes the largest death toll among environmental risks globally, but interventions to purify ambient air remain inadequate. Vegetation and green spaces have shown reductive effects on air-borne pollutants concentrations, especially of particulate matter (PM). Guidance on green space utilisation for air quality control remains scarce, however, as does its application in practise. To strengthen the foundation for research and interventions, we undertook a critical review of the state of science from a public health perspective. We used inter-disciplinary search strategies for published reviews on green spaces and air pollution in key scientific databases. Using the PRISMA checklist, we systematically identified reviews with quantitative analyses. For each of the presented PM mitigation mechanisms, we conducted additional searches focused on the most recent articles published between 2016 and early 2021. The included reviews differentiate three mitigation mechanisms of green spaces for PM: deposition, dispersion and modification. The most studied mechanism is deposition, particularly measures of mass and settling velocity of PM on plant leaves. We consolidate how green space setups differ by scale and context in their potentials to reduce peak exposures, stationary (point) or mobile (line) pollution sources, and the potentially most harmful PM components. The assessed findings suggest diverse optimisation options for green space interventions, particularly concerning plant selection, spatial setup, ventilation and maintenance - all alongside the consideration of supplementary vegetation effects like on temperature or water. Green spaces' reductive effects on air-borne PM concentrations are considerable, multi-mechanistic and varied by scale, context and vegetation characteristics. Such effect-modifying factors must be considered when rethinking public space design, as accelerated by the COVID-19 pandemic. Weak linkages amid involved disciplines motivate the development of a research framework to strengthen health-oriented guidance. We conclude on an urgent need for an integrated and risk-based approach to PM mitigation through green space interventions.

3D Spatial Analysis of Particulate Matter (PM10, PM2.5 and PM1.0) and Gaseous Pollutants (H2S, SO2 and VOC) in Urban Areas Surrounding a Large Heat and Power Plant

In many regions of the world, the winter period is a time of poor air quality, due primarily to the increased use of individual and district heating systems. As a consequence, the atmospheric air contains increased concentrations of both particulate matter and gaseous pollutants (as a result of “low” emissions at altitudes of up to 40 m and “high” emissions more than 40 m above ground level). In winter, the increased pollution is very often exacerbated by meteorological conditions, including air temperature, pressure, air speed, wind direction, and thermal inversion. Here, we analyze the concentrations of particulate matter (PM10, PM2.5, and PM1.0) and gaseous pollutants (H2S, SO2, and VOC) in the immediate vicinity of a large solid fuel-fired heat and power plant located in an urban agglomeration. Two locations were selected for analysis. The first was close to an air quality measurement station in the center of a multi-family housing estate. The second was the intersection of two main communication routes. To determine the impact of “low” and “high” emissions on air quality, the selected pollutants were measured at heights of between 2 and 50 m using an unmanned aerial vehicle. The results were compared with permissible standards for the concentration of pollutants. Temperature inversion was found to have a strong influence on the level of pollutants at various heights, with higher concentrations of particulate matter registered at altitudes above 40 m. The source of PM, H2S, and SO2 pollutants was confirmed to be “low emission” from local transport, industrial plant areas, and the housing estate comprising detached houses located in the vicinity of the measuring points. “High emission” was found to be responsible for the high concentrations of VOC at altitudes of more than 40 m above the intersection and in the area of the housing estate.

Application of an emission profile-based method to trace the sources of volatile organic compounds in a chemical industrial park

The accurate source tracing of volatile organic compounds (VOCs) in complicated source environments is challenging to perform, as similar pollutants may be emitted from different chemical processes. An emission profile-based source tracing method, based on comparing similarities between source profiles and ambient air profiles, was evaluated, and was found to improve the tracing efficiency. Emission profiles were acquired from a typical chemical industrial park in the Yangtze River Delta, China. A total of 30 process-based emission profiles comprising 107 VOC species were investigated and similarities among them were calculated. This analysis demonstrated that the similarities between emissions from various chemical processes are universal. Source tracing was then conducted for six air pollution episodes, based on the emission profile-based source tracing method combined with wind speed and direction data. The results showed that the proposed approach represents an efficient method for source tracing. This study enriches the database of source profiles for petroleum-related industries. The emission profiles from references and the air pollution episodes augment the emission profile database, especially under abnormal emission conditions. The database will more effectively serve future source-tracing cases, creating a virtuous circle that improves source tracing efficiency.

New approaches for modeling the regional pollution in Europe

Generally, official statistical reports provide information on the pollution extent over a region using the average records from all the observation sites. In the outliers' presence, the average is not a good choice. Therefore, in this article, we propose two alternatives for replacing the average series by most significant regional series, obtained by two selection procedures. The first algorithm chooses the candidates to be utilized for the regional estimation of pollution by a data segmentation that provides the most representative value for a given time interval. Since the number of segments to be used should be prior introduced, the second algorithm proposes a version of the selection procedure based on the k-means algorithm. The performances of these methods are verified on three groups of series (carbon oxides, sulfur oxides, and nitrogen oxides) recorded in the EEA33 countries during a period of 28 years. Both algorithms give better results than the average series, in terms of mean standard errors (MSE) and mean absolute errors (MAE).

Spatial Analysis (Measurements at Heights of 10 m and 20 m above Ground Level) of the Concentrations of Particulate Matter (PM10, PM2.5, and PM1.0) and Gaseous Pollutants (H2S) on the University Campus: A Case Study

Spatial analysis of the distribution of particulate matter PM10, PM2.5, PM1.0, and hydrogen sulfide (H2S) gas pollution was performed in the area around a university library building. The reasons for the subject matter were reports related to the perceptible odor characteristic of hydrogen sulfide and a general poor assessment of air quality by employees and students. Due to the area of analysis, it was decided to perform measurements at two heights, 10 m and 20 m above ground level, using measuring equipment attached to a DJI Matrice 600 unmanned aerial vehicle (UAV). The aim of the measurements was air quality assessment and investigate the convergence of the theory of air flow around the building with the spatial distribution of air pollutants. Considerable differences of up to 63% were observed in the concentrations of pollutants measured around the building, especially between opposite sides, depending on the direction of the wind. To explain these differences, the theory of aerodynamics was applied to visualize the probable airflow in the direction of the wind. A strong convergence was observed between the aerodynamic model and the spatial distribution of pollutants. This was evidenced by the high concentrations of dust in the areas of strong turbulence at the edges of the building and on the leeward side. The accumulation of pollutants was also clearly noticeable in these locations. A high concentration of H2S was recorded around the library building on the side of the car park. On the other hand, the air turbulence around the building dispersed the gas pollution, causing the concentration of H2S to drop on the leeward side. It was confirmed that in some analyzed areas the permissible concentration of H2S was exceeded.

Urban wind field analysis from the Jack Rabbit II Special Sonic Anemometer Study

The Jack Rabbit II Special Sonic Anemometer Study (JRII-S), a field project designed to examine the flow and turbulence within a systematically arranged mock-urban environment constructed from CONEX shipping containers, is described in detail. The study involved the deployment of 35 sonic anemometers at multiple heights and locations, including a 32 m tall, unobstructed tower located about 115 m outside the building array to document the approach wind flow characteristics. The purpose of this work was to describe the experimental design, analyze the sonic data, and report observed wind flow patterns within the urban canopy in comparison to the approaching boundary layer flow. We show that the flow within the building array follows a tendency towards one of three generalized flow regimes displaying channeling over a wide range of wind speeds, directions, and stabilities. Two or more sonic anemometers positioned only a few meters apart can have vastly different flow patterns that are dictated by the building structures. Within the building array, turbulence values represented by normalized vertical velocity variance ( σ w 2 ) are at least two to three times greater than that in the approach flow. There is also little evidence that σ w 2 measured at various heights or locations within the JRII array is a strong function of stability type in contrast to the approach flow. The results reinforce how urban areas create complicated wind patterns, channeling effects, and localized turbulence that can impact the dispersion of an effluent release. These findings can be used to inform the development of improved wind flow algorithms to better characterize pollutant dispersion in fast-response models.

Aerosol Transmission of SARS-CoV-2: Physical Principles and Implications

Evidence has emerged that SARS-CoV-2, the coronavirus that causes COVID-19, can be transmitted airborne in aerosol particles as well as in larger droplets or by surface deposits. This minireview outlines the underlying aerosol science, making links to aerosol research in other disciplines. SARS-CoV-2 is emitted in aerosol form during normal breathing by both asymptomatic and symptomatic people, remaining viable with a half-life of up to about an hour during which air movement can carry it considerable distances, although it simultaneously disperses. The proportion of the droplet size distribution within the aerosol range depends on the sites of origin within the respiratory tract and on whether the distribution is presented on a number or volume basis. Evaporation and fragmentation reduce the size of the droplets, whereas coalescence increases the mean droplet size. Aerosol particles containing SARS-CoV-2 can also coalesce with pollution particulates, and infection rates correlate with pollution. The operation of ventilation systems in public buildings and transportation can create infection hazards via aerosols, but provides opportunities for reducing the risk of transmission in ways as simple as switching from recirculated to outside air. There are also opportunities to inactivate SARS-CoV-2 in aerosol form with sunlight or UV lamps. The efficiency of masks for blocking aerosol transmission depends strongly on how well they fit. Research areas that urgently need further experimentation include the basis for variation in droplet size distribution and viral load, including droplets emitted by "superspreader" individuals; the evolution of droplet sizes after emission, their interaction with pollutant aerosols and their dispersal by turbulence, which gives a different basis for social distancing.

Mathematical Modeling and Simulation of a Gas Emission Source Using the Network Simulation Method

A mathematical model for the simulation of the diffusion of the pollutants released from a point source is presented. All phenomena have been included, such as thermal and wind gradients, turbulence, fumigation, convective and diffusive effects, and atmospheric stabilities. To better understand the dynamics of these occurrences, the Network Simulation Method was used to provide the concentration of pollutants in three spatial coordinates. The model was simulated in open source software and validated with experimental data, satisfying the Hanna criteria. Additionally, this model selects for the appropriate expressions based on the physical phenomena that govern each case and allows for time-dependent data entry. The cases studied show the great coupling that exists between the variables of wind velocity and atmospheric stability for the pollutant diffusion. The model can be used for two important aims, to identify the behavior of the emission of pollutants, and to determine the concentration of a pollutant at various points, through an inverse problem, locating the source of the emission.

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

In this study, we have assessed the three-dimensional (3-D) spatial extent of near-road air pollution around a signalized intersection in a densely populated area using collaborating methodologies of stationary measurements, drone monitoring, and atmospheric dispersion modeling. Stationary measurement data collected in the roadside apartment building showed a substantial effect of emitted pollutants, such as nitrogen oxides (NO_x), black carbon (BC), and ultrafine particles (UFPs), especially during the morning rush hours. Vertical drone monitoring near the road intersection exhibited a steeper decreasing trend with increasing altitude for BC concentration rather than for fine particulate matter (PM_2.5) concentration below the apartment building height. Atmospheric NO_x dispersion was simulated using the weather research and forecasting (WRF) and computational fluid dynamics (CFD) models for the drone measurement periods. Based on the agreement between the measured BC and simulated NO_x concentrations, we concluded that the air pollution around the road intersection has adverse effects on the health of residents living within the 3-D spatial extent within at least 120 m horizontally and a half of building height vertically during the morning rush hours. The comparability between drone monitoring and WRF-CFD modeling can further guarantee the identification of air pollution hotspots using the methods.

High-resolution simulation of local traffic-related NOx dispersion and distribution in a complex urban terrain

Urban air pollution features large spatial and temporal variations due to the high heterogeneity in emissions and ventilation conditions, which render the pollutant distributions in complex urban terrains difficult to measure. Current urban air pollution models are not able to simulate pollutant dispersion and distribution at a low computational cost and high resolution. To address this limitation, we have developed the urban terrain air pollution (UTAP) dispersion model to investigate, at a spatial resolution of 5 m and a temporal resolution of 1 h, the distribution of the local traffic-related NO_x concentration at the pedestrian level in a 1 × 1 km² area in Baoding, Hebei, China. The UTAP model was shown to be capable of capturing the local pollution variations in a complex urban terrain at a low computational cost. We found that the local traffic-related NO_x concentration along or near major roads (10-200 μg m^-3) was 1-2 orders of magnitude higher than that in places far from roads (0.1-10 μg m^-3). Considering the background pollution, the NO and NO₂ concentrations exhibited similar patterns with higher concentrations in street canyons and lower concentrations away from streets, while the O₃ concentration exhibited the opposite behavior. Sixty percent of the NO_x concentration likely stemmed from local traffic when the background pollution level was low. Both the background wind speed and direction substantially impacted the overall pollution level and concentration variations, with a low wind speed and direction perpendicular to the axes of most streets identified as unfavorable pollutant dispersion conditions. Our results revealed a large variability in the local traffic-related air pollutant concentration at the pedestrian level in the complex urban terrain, indicating that high-resolution computationally efficient models such as the UTAP model are required to accurately estimate the pollutant exposure of urban residents.

Turbulent Flows and Pollution Dispersion around Tall Buildings Using Adaptive Large Eddy Simulation (LES)

The motivation for this work stems from the increased number of high-rise buildings/skyscrapers all over the world, and in London, UK, and hence the necessity to see their effect on the local environment. We concentrate on the mean velocities, Reynolds stresses, turbulent kinetic energies (TKEs) and tracer concentrations. We look at their variations with height at two main locations within the building area, and downstream the buildings. The pollution source is placed at the top of the central building, representing an emission from a Combined Heat and Power (CHP) plant. We see how a tall building may have a positive effect at the lower levels, but a negative one at the higher levels in terms of pollution levels. Mean velocities at the higher levels (over 60 m in real life) are reduced at both locations (within the building area and downstream it), whilst Reynolds stresses and TKEs increase. However, despite the observed enhanced turbulence at the higher levels, mean concentrations increase, indicating that the mean flow has a greater influence on the dispersion. At the lower levels (Z < 60 m), the presence of a tall building enhanced dispersion (hence lower concentrations) for many of the configurations.

On the Convergence and Capability of the Large-Eddy Simulation of Concentration Fluctuations in Passive Plumes for a Neutral Boundary Layer at Infinite Reynolds Number

Large-eddy simulation (LES) experiments have been performed using the Parallelized LES Model (PALM). A methodology for validating and understanding LES results for plume dispersion and concentration fluctuations in an atmospheric-like flow is presented. A wide range of grid resolutions is shown to be necessary for investigating the convergence of statistical characteristics of velocity and scalar fields. For the scalar, the statistical moments up to the fourth order and the shape of the concentration probability density function (p.d.f.) are examined. The mean concentration is influenced by grid resolution, with the highest resolution simulation showing a lower mean concentration, linked to larger turbulent structures. However, a clear tendency to convergence of the concentration variance is observed at the two higher resolutions. This behaviour is explained by showing that the mechanisms driving the mean and the variance are differently influenced by the grid resolution. The analysis of skewness and kurtosis allows also the obtaining of general results on plume concentration fluctuations. Irrespective of grid resolution, a family of Gamma p.d.f.s well represents the shape of the concentration p.d.f. but only beyond the peak of the concentration fluctuation intensity. In the early plume dispersion phases, the moments of the p.d.f. are in good agreement with those generated by a fluctuating plume model. To the best of our knowledge, our study demonstrates for the first time that, if resolution and averaging time are adequate, atmospheric LES provides a trustworthy representation of the high order moments of the concentration field, up to the fourth order, for a dispersing plume.

High-Efficiency Simulation Framework to Analyze the Impact of Exhaust Air from COVID-19 Temporary Hospitals and its Typical Applications

The outbreak of COVID-19 resulted in severe pressure on the existing medical infrastructure in China. Several Chinese cities began to construct temporary hospitals for the centralized treatment of COVID-19 patients. The harmful exhaust air from the outlets of these hospitals may have a significant adverse impact on the fresh-air intakes and surrounding environment. Owing to the need to rapidly construct these hospitals within 6–10 days, just a few hours are allowed for the analysis of the impact of this exhaust air on the environment. To overcome this difficulty, a high-efficiency simulation framework is proposed in this study. Based on the open-source computational fluid dynamics software, FDS, the proposed framework is adaptive and incorporates building information with different levels of detail during various design phases of the hospital, and has been applied in the design of the Wuhan Huoshenshan Hospital, the first typical COVID-19 temporary hospital in China. According to the simulation results, neither the fresh-air intakes nor the surrounding buildings would be polluted by the harmful air discharged from the air outlets of the Huoshenshan hospital. The proposed simulation framework can provide a reference for the design and overall planning of similar hospitals in China and other affected countries.

Investigation into the effect of upstream obstacles and hazardous sources on dispersion in the urban environment with LES model

The release of hazardous materials originated from industrial/natural accidents or intentional attacks within a compact urban environment can be disastrous. Once released, the hazardous pollutants will be dispersed through the atmosphere instantaneously and threaten human health. This study aims at evaluating the overall effect of upstream obstacles and hazardous sources on the downstream targets through parametric investigations. A complex building morphology composed of obstacle group, target group, one main street canyon and several subsidiary street canyons is proposed. The dimensional parameters along with the sources are set as variables. An orthogonal numerical test with Large Eddy Simulation (LES) model is carried out, indicating that the source conditions play a more important role than the obstacles dimension in pollutants accumulation around targets. The flow and dispersion structures are categorized into five patterns, which are strongly relevant to the dimension parameters. Due to the upstream perturbation, the sidewalls of targets are found to be contaminated more seriously than the obstacles, while both their windward and leeward walls have a lower concentration of pollutants.

Effect of pollutant source location on air pollutant dispersion around a high-rise building

This article investigates the dispersion of airborne pollutants emitted from different locations near a high-rise building. A Computational Fluid Dynamics (CFD) model for simulating the wind flow field and the pollutant dispersion was developed and validated by wind tunnel data. Then the spreading of the pollutant emitted from different locations to a rectangular-shaped high-rise residential (HRR) building was numerically studied. The pollutant source location was set in a wide range of the position angle and distance between the source and the building. It was found that the pollutant concentration on the building decreases with an increase in the emission distance whereas the effect of the position angle is more complicated. Interestingly, there is a critical range of the position angle from which the emitted pollutants will not spread to the building in a significant way. The effect of the source location was linked to the wind flow field around the building, particularly with several major flows. The vertical distributions of the pollutant concentration on different faces were also investigated, and it was found that these are more affected by the vertical flow near each face. Finally, a mathematical model was developed to evaluate the pollutant concentration as a function of the emission distance and position angle. These findings are helpful to the understanding of the dispersion of airborne pollutants around high-rise buildings and the related hazard management in urban design.

Numerical Simulation of Haze-Fog Particle Dispersion in the Typical Urban Community by Using Discrete Phase Model

The haze-fog particle dispersion in urban communities will cause serious health and environmental problems, which has aroused society attention. The aim of the present investigation is to reveal the underlying mechanisms of haze-fog particle dispersion via Computational Fluid Dynamics (CFD) method, and then to provide a groundwork for the optimal spatial arrangement of urban architecture. The Delayed Detached-eddy Simulation turbulence model (DDES) and Discrete Phase Model (DPM) are utilized to investigate the wind flow distribution and the particle dispersion around the building group. The numerical results show that the particle dispersion is dominated by the incoming wind flow, the layout of architectural space and the type and distribution of vortex. The ‘single body’ wake pattern and the vortex impingement wake pattern are identified in the wind flow field, which have different effects on the distribution of haze-fog particle. The cavity formed by the layout of the building group induces primary vortex and secondary vortex, which will make it more difficult for the particles entering the square cavity to flow out. Moreover, the concentration of the particle in the rear of the buildings is relatively low due the effect of attached vortices.

Heterogeneous Computing (CPU–GPU) for Pollution Dispersion in an Urban Environment

The use of Computational Fluid Dynamics (CFD) to assist in air quality studies in urban environments can provide accurate results for the dispersion of pollutants. However, due to the computational resources needed, simulation domain sizes tend to be limited. This study aims to improve the computational efficiency of an emission and dispersion model implemented in a CPU-based solver by migrating it to a CPU–GPU-based one. The migration of the functions that handle boundary conditions and source terms for the pollutants is explained, as well as the main differences present in the solvers used. Once implemented, the model was used to run simulations with both engines on different platforms, enabling the comparison between them and reaching promising time improvements in favor of the use of GPUs.

Reduction of particulate matter concentrations by local removal in a building courtyard: Case study for the Delhi American Embassy School

Exposure to particulate matter (PM) is strongly linked to human morbidity and mortality, where higher exposure entails higher all-cause daily mortality and increased long-term risk of cardiopulmonary mortality. The objective of this study is to demonstrate how and to what extent the local removal of PM_2.5 can lead to reduced exposure for the children and teachers in the naturally ventilated courtyard of the American Embassy School (AES) high school building in Delhi. The study is performed by computational fluid dynamics (CFD) with the 3D steady Reynolds-averaged Navier-Stokes (RANS) equations in combination with the realizable k-ε turbulence model on a very high resolution grid. First, CFD validation is performed using wind-tunnel experiments of the flow pattern in and above a generic single street canyon. Next, the case study is conducted where four commercially available electrostatic precipitation (ESP) units are installed at different positions inside the courtyard and the resulting performance is evaluated. PM_2.5 dispersion is modeled with an Eulerian advection-diffusion equation. It is shown that the best ESP positions yield overall volume-averaged PM_2.5 concentration reductions up to 34.1% in the courtyard's corridors, demonstrating the proposed mitigation strategy to be effective. Perspectives for further reduction of the PM concentrations and the related reduction of health risks are discussed.

Effect of Local Grid Refinement on Performance of Scale-Resolving Models for Simulation of Complex External Flows

Numerical simulations are crucial for fast and accurate estimations of the flow characteristics in many engineering applications such as atmospheric boundary layers around buildings, external aerodynamics around vehicles, and pollutant dispersion. In the simulation of flow over urban-like obstacles, it is crucial to accurately resolve the flow characteristics with reasonable computational cost. Therefore, Large Eddy Simulations on non-uniform grids are usually employed. However, an undesirable accumulation of energy at grid-refinement interfaces was observed in previous studies using non-uniform grids. This phenomenon induced oscillations in the spanwise velocity component, mainly on fine-to-coarse grid interfaces. In this study, the two challenging test cases of flow over urban-like cubes and flow over a 3-D circular cylinder were simulated using three different scale-resolving turbulence models. Simulations were performed on uniform coarse and fine grids on one hand, and a non-uniform grid on the other, to assess the effect of mesh density and mesh interfaces on the models’ performance. Overall, the proposed One-Equation Scale-Adaptive Simulation (One-Equation SAS) showed the least deviation from the experimental results in both tested cases and on all grid sizes and types when compared to the Shear Stress Transport-Improved Delayed Detached Eddy Simulation (IDDES) and the Algebraic Wall-Modeled Large Eddy Simulation (WMLES).

Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models

Green infrastructure (GI) in urban areas may be adopted as a passive control system to reduce air pollutant concentrations. However, current dispersion models offer limited modelling options to evaluate its impact on ambient pollutant concentrations. The scope of this review revolves around the following question: how can GI be considered in readily available dispersion models to allow evaluation of its impacts on pollutant concentrations and health risk assessment? We examined the published literature on the parameterisation of deposition velocities and datasets for both particulate matter and gaseous pollutants that are required for deposition schemes. We evaluated the limitations of different air pollution dispersion models at two spatial scales - microscale (i.e. 10-500 m) and macroscale (i.e. 5-100 km) - in considering the effects of GI on air pollutant concentrations and exposure alteration. We conclude that the deposition schemes that represent GI impacts in detail are complex, resource-intensive, and involve an abundant volume of input data. An appropriate handling of GI characteristics (such as aerodynamic effect, deposition of air pollutants and surface roughness) in dispersion models is necessary for understanding the mechanism of air pollutant concentrations simulation in presence of GI at different spatial scales. The impacts of GI on air pollutant concentrations and health risk assessment (e.g., mortality, morbidity) are partly explored. The i-Tree tool with the BenMap model has been used to estimate the health outcomes of annually-averaged air pollutant removed by deposition over GI canopies at the macroscale. However, studies relating air pollution health risk assessments due to GI-related changes in short-term exposure, via pollutant concentrations redistribution at the microscale and enhanced atmospheric pollutant dilution by increased surface roughness at the macroscale, along with deposition, are rare. Suitable treatments of all physical and chemical processes in coupled dispersion-deposition models and assessments against real-world scenarios are vital for health risk assessments.

Vertical monitoring of traffic-related air pollution (TRAP) in urban street canyons of Hong Kong

Rapid urbanization has significantly increased air pollution especially in urban regions with high traffic volumes. Existing methods for estimating traffic-related air pollution (TRAP) and TRAP-related health impacts are based on two-dimensional modelling. This paper describes a point-based methodology to monitor vertical pollutant concentrations in typical street canyons of Hong Kong. It explains the conceptual design, monitoring strategy and selection criteria for a limited number of receptor locations in street canyons to undertake field measurements for both outdoor exposure and indoor infiltration. It also expounds on the limitations and complications associated with field instrumentation and retention of participating home units. The empirical results were applied on the building infiltration efficiencies assessment. It is concluded that the cost-effective field methodology developed in this paper expects to strike a balance between exposure error and limited data locations. These findings will have important implications in future monitoring design of vertical TRAP exposure to support health studies.

Ozone source apportionment during peak summer events over southwestern Europe

It is well established that in Europe, high O₃ concentrations are most pronounced in southern/Mediterranean countries due to the more favourable climatological conditions for its formation. However, the contribution of the different sources of precursors to O₃ formation within each country relative to the imported (regional and hemispheric) O₃ is poorly quantified. This lack of quantitative knowledge prevents local authorities from effectively designing plans that reduce the exceedances of the O₃ target value set by the European air quality directive. O₃ source attribution is a challenge because the concentration at each location and time results not only from local biogenic and anthropogenic precursors, but also from the transport of O₃ and precursors from neighbouring regions, O₃ regional and hemispheric transport and stratospheric O₃ injections. The main goal of this study is to provide a first quantitative estimation of the contribution of the main anthropogenic activity sectors to peak O₃ events in Spain relative to the contribution of imported (regional and hemispheric) O₃. We also assess the potential of our source apportionment method to improve O₃ modelling. Our study applies and thoroughly evaluates a countrywide O₃ source apportionment method implemented in the CALIOPE air quality forecast system for Spain at high resolution (4 × 4 km²) over a 10-day period characterized by typical summer conditions in the Iberian Peninsula (IP). The method tags both O₃ and its gas precursor emissions from source sectors within one simulation, and each tagged species is subject to the typical physico-chemical processes (advection, vertical mixing, deposition, emission and chemistry) as the actual conditions remain unperturbed. We quantify the individual contributions of the largest NO _x local sources to high O₃ concentrations compared with the contribution of imported O₃. We show, for the first time, that imported O₃ is the largest input to the ground-level O₃ concentration in the IP, accounting for 46 %-68 % of the daily mean O₃ concentration during exceedances of the European target value. The hourly imported O₃ increases during typical northwestern advections (70 %-90 %, 60-80 μg m^-3), and decreases during typical stagnant conditions (30 %-40 %, 30-60 μg m^-3) due to the local NO titration. During stagnant conditions, the local anthropogenic precursors control the O₃ peaks in areas downwind of the main urban and industrial regions (up to 40 % in hourly peaks). We also show that ground-level O₃ concentrations are strongly affected by vertical mixing of O₃-rich layers present in the free troposphere, which result from local/regional layering and accumulation, and continental/hemispheric transport. Indeed, vertical mixing largely explains the presence of imported O₃ at ground level in the IP. Our results demonstrate the need for detailed quantification of the local and remote contributions to high O₃ concentrations for local O₃ management, and show O₃ source apportionment to be an essential analysis prior to the design of O₃ mitigation plans in any non-attainment area. Achieving the European O₃ objectives in southern Europe requires not only ad hoc local actions but also decided national and European-wide strategies.

Numerical evaluations of urban design technique to reduce vehicular personal intake fraction in deep street canyons

High-rise deep street canyons usually experience poor ventilation and large vehicular pollutant exposure to residents in near-road buildings. Investigations are still required to clarify the flow and dispersion mechanisms in deep street canyons and explore techniques to reduce such large pollutant exposure. By conducting computational fluid dynamics (CFD) simulations validated by wind tunnel data and scale-model outdoor field measurements, we investigate the integrated impacts of aspect ratios, first-floor and second-floor elevated building designs, viaduct settings, height variations and wind catchers on the flow, personal intake fraction (P_IF) of CO (carbon dioxide) and its spatial mean value 〈P_IF〉 in two-dimensional (2D) street canyons. Results show that cases with H/W = 5 experience two counter-rotating vortices, much poorer ventilation and 1-2 orders larger 〈P_IF〉 (43.6-120.8 ppm) than H/W = 1 and 3 (3.8-4.3 and 5.6-5.8 ppm). Moreover, in cases with H/W = 5 the height variation results in three vertically-aligned vortices and much weaker wind, subsequently produces greater 〈P_IF〉 (1402-2047 ppm). To reduce 〈P_IF〉 with H/W = 5, various urban designs are evaluated. The first-floor elevated building design creates more effective ventilation pathways than the second-floor elevated type does and reduces 〈P_IF〉 at H/W = 5 by five orders (1402 to ~0.01 ppm) or two orders (43.6 to ~0.1 ppm) in cases with or without the height variation. However, such reductions at H/W = 1 and 3 are only 76.8%-81.4% and 22.4%-36.2% respectively. Wind catchers destroy the multi-vortex flow pattern as H/W = 5, produce a contra-clockwise main vortex and reduce 〈P_IF〉 by 1-2 orders for cases with or without the height variation.

Improving one-dimensional pollution dispersion modeling in rivers using ANFIS and ANN-based GA optimized models

Simulation and prediction of the pollution transport is one of the major problems in environmental and rivers engineering studies. The numerical tools have been used in simulation of the concentration profile transmission for description of river water quality. The one-dimensional advection-dispersion equation (ADE) is used in applied water quality modeling and requires the accurate estimation of longitudinal dispersion coefficient (D_x). This paper develops a hybrid numerical-intelligence model for dispersion modeling in open-channel flows. The main contribution of this paper is to improve the results of 1D numerical simulation of pollutant transport in steady flows by estimation of dispersion coefficient (D_x) based on artificial intelligence models and subset selection of maximum dissimilarity (SSMD). The developed hybrid model uses an intelligence module based on optimized adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANNs) for longitudinal dispersion estimation, in which their structures are optimized by genetic algorithm (GA). Intelligence estimates of D_x by ANN, ANFIS, ANFIS-GA, ANN-GA, multiple linear regression (MLR), and empirical equation are compared with observed values of D_x available in 505 river section, and the ANFIS-GA, as the most accurate, is incorporated and integrated with developed 1D-ADE numerical module. The numerical solution of 1D-ADE is done using physically influenced scheme (PIS) for face flux estimation in finite volume method. The performance of hybrid models PIS-ANFIS-GA, PIS-ANFIS, and PIS-empirical is compared using the R², RMSE, MAE, and NSE values in comparison with analytical solution and measured concentration hydrographs. The results revealed that the hybrid numerical-intelligence model is more accurate than the other classical methods for sediment/pollutant dispersion prediction in open-channel flows. The developed hybrid numerical-intelligence model can accurately simulate the dispersion processes in rivers and is a novel step in applicability of ANFIS-GA and ANN-GA models. Graphical abstract ᅟ.

A review of numerical models to predict the atmospheric dispersion of radionuclides

The field of atmospheric dispersion modeling has evolved together with nuclear risk assessment and emergency response systems. Atmospheric concentration and deposition of radionuclides originating from an unintended release provide the basis of dose estimations and countermeasure strategies. To predict the atmospheric dispersion and deposition of radionuclides several numerical models are available coupled with numerical weather prediction (NWP) systems. This work provides a review of the main concepts and different approaches of atmospheric dispersion modeling. Key processes of the atmospheric transport of radionuclides are emission, advection, turbulent diffusion, dry and wet deposition, radioactive decay and other physical and chemical transformations. A wide range of modeling software are available to simulate these processes with different physical assumptions, numerical approaches and implementation. The most appropriate modeling tool for a specific purpose can be selected based on the spatial scale, the complexity of meteorology, land surface and physical and chemical transformations, also considering the available data and computational resource. For most regulatory and operational applications, offline coupled NWP-dispersion systems are used, either with a local scale Gaussian, or a regional to global scale Eulerian or Lagrangian approach. The dispersion model results show large sensitivity on the accuracy of the coupled NWP model, especially through the description of planetary boundary layer turbulence, deep convection and wet deposition. Improvement of dispersion predictions can be achieved by online coupling of mesoscale meteorology and atmospheric transport models. The 2011 Fukushima event was the first large-scale nuclear accident where real-time prognostic dispersion modeling provided decision support. Dozens of dispersion models with different approaches were used for prognostic and retrospective simulations of the Fukushima release. An unknown release rate proved to be the largest factor of uncertainty, underlining the importance of inverse modeling and data assimilation in future developments.

Impact of roof height non-uniformity on pollutant transport between a street canyon and intersections

This paper presents an extension of our previous wind-tunnel study (Nosek et al., 2016) in which we highlighted the need for investigation of the removal mechanisms of traffic pollution from all openings of a 3D street canyon. The extension represents the pollution flux (turbulent and advective) measurements at the lateral openings of three different 3D street canyons for the winds perpendicular and oblique to the along-canyon axis. The pollution was simulated by emitting a passive gas (ethane) from a homogeneous ground-level line source positioned along the centreline of the investigated street canyons. The street canyons were formed by courtyard-type buildings of two different regular urban-array models. The first model has a uniform building roof height, while the second model has a non-uniform roof height along each building's wall. The mean flow and concentration fields at the canyons' lateral openings confirm the findings of other studies that the buildings' roof-height variability at the intersections plays an important role in the dispersion of the traffic pollutants within the canyons. For the perpendicular wind, the non-uniform roof-height canyon appreciably removes or entrains the pollutant through its lateral openings, contrary to the uniform canyon, where the pollutant was removed primarily through the top. The analysis of the turbulent mass transport revealed that the coherent flow structures of the lateral momentum transport correlate with the ventilation processes at the lateral openings of all studied canyons. These flow structures coincide at the same areas and hence simultaneously transport the pollutant in opposite directions.

Ranking current and prospective NO2 pollution mitigation strategies: An environmental and economic modelling investigation in Oxford Street, London

Air pollution continues to be a problem in the urban environment. A range of different pollutant mitigation strategies that promote dispersion and deposition exist, but there is little evidence with respect to their comparative performance from both an environmental and economic perspective. This paper focuses on examining different NO₂ mitigation strategies such as trees, buildings facades coated with photocatalytic paint and solid barriers in Oxford Street in London. The case study findings will support ranking the environmental and economic impacts of these different strategies to improve personal exposure conditions on the footpath and on the road in a real urban street canyon. CFD simulations of airflow and NO₂ dispersion in Oxford Street in London were undertaken using the OpenFOAM software platform with the k-ε model, taking into account local prevailing wind conditions. Trees are shown to be the most cost-effective strategy, with a small reduction in NO₂ concentrations of up to 0.7% on the road. However, solid barriers with and without the application of photocatalytic paint and an innovative material (20 times more expensive than trees) can improve air quality on the footpaths more substantially, up to 7.4%, yet this has a significant detrimental impact on NO₂ concentrations (≤23.8%) on the road. Photocatalytic paint on building surfaces presented a minimal environmental reductions (1.2%) and economic (>100 times more expensive than trees) mitigation strategy. The findings recognised the differences between footpath and road concentrations occurred and that a focused examination of three pollution hotspots can provide more cost effective pollution mitigation. This study considers how a number of pollutant mitigation measures can be applied in a single street canyon and demonstrates the strengths and weaknesses of these strategies from economic and environmental perspectives. Further research is required to extrapolate the findings presented here to different street geometries.

Simulation of gaseous pollutant dispersion around an isolated building using the k-ω SST (shear stress transport) turbulence model

The dispersion of gaseous pollutant around buildings is complex due to complex turbulence features such as flow detachment and zones of high shear. Computational fluid dynamics (CFD) models are one of the most promising tools to describe the pollutant distribution in the near field of buildings. Reynolds-averaged Navier-Stokes (RANS) models are the most commonly used CFD techniques to address turbulence transport of the pollutant. This research work studies the use of [Formula: see text] closure model for the gas dispersion around a building by fully resolving the viscous sublayer for the first time. The performance of standard [Formula: see text] model is also included for comparison, along with results of an extensively validated Gaussian dispersion model, the U.S. Environmental Protection Agency (EPA) AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model). This study's CFD models apply the standard [Formula: see text] and the [Formula: see text] turbulence models to obtain wind flow field. A passive concentration transport equation is then calculated based on the resolved flow field to simulate the distribution of pollutant concentrations. The resultant simulation of both wind flow and concentration fields are validated rigorously by extensive data using multiple validation metrics. The wind flow field can be acceptably modeled by the [Formula: see text] model. However, the [Formula: see text] model fails to simulate the gas dispersion. The [Formula: see text] model outperforms [Formula: see text] in both flow and dispersion simulations, with higher hit rates for dimensionless velocity components and higher "factor of 2" of observations (FAC2) for normalized concentration. All these validation metrics of [Formula: see text] model pass the quality assurance criteria recommended by The Association of German Engineers (Verein Deutscher Ingenieure, VDI) guideline. Furthermore, these metrics are better than or the same as those in the literature. Comparison between the performances of [Formula: see text] and AERMOD shows that the CFD simulation is superior to Gaussian-type model for pollutant dispersion in the near wake of obstacles. AERMOD can perform as a screening tool for near-field gas dispersion due to its expeditious calculation and the ability to handle complicated cases. The utilization of [Formula: see text] to simulate gaseous pollutant dispersion around an isolated building is appropriate and is expected to be suitable for complex urban environment.

IMPLICATIONS

Multiple validation metrics of [Formula: see text] turbulence model in CFD quantitatively indicated that this turbulence model was appropriate for the simulation of gas dispersion around buildings. CFD is, therefore, an attractive alternative to wind tunnel for modeling gas dispersion in urban environment due to its excellent performance, and lower cost.

Numerical investigations of flow and passive pollutant exposure in high-rise deep street canyons with various street aspect ratios and viaduct settings

Vehicular pollutant exposure of residents and pedestrians in high-rise deep street canyons with viaducts and noise barriers requires special concerns because the ventilation capacity is weak and the literature reported inconsistent findings on flow patterns as aspect ratios (building height/street width, H/W) are larger than 2. By conducting computational fluid dynamics (CFD) simulations coupled with the intake fraction iF and the daily pollutant exposure E_t, this paper investigates the impact of street aspect ratios, viaducts and noise barriers on the flow and vehicular passive pollutant exposure in full-scale street canyons (H/W=1-6, W=24m). iF represents the fraction of total emissions inhaled by a population (1ppm=10^-6), while E_t means the extent of human beings' contact with pollutants within one day. CFD methodologies of passive pollutant dispersion modeling are successfully validated by wind tunnel data in Meroney et al. (1996). As a novelty, the two-main-vortex pattern start appearing in full-scale street canyons as H/W changes from 4 to 5, however previous studies using wind-tunnel-scale models (H=6cm) reported two to five vortexes as H/W=2-5. This finding is validated by both smoke visualization in scale-model outdoor field experiments (H=1.2m, W=0.6m) and CFD simulations of Reynolds number independence. Cases with two main vortexes (H/W=5-6) experience much larger daily pollutant exposure (~10³-10⁴mg/m³/day) than those with single main vortex as H/W=1-4 (~10¹-10²mg/m³/day). Moreover leeward-side pollutant exposures are much larger than windward-side as H/W=1-4 while oppositely as H/W=5-6. Assuming a general population density, the total iF is 485-803ppm as H/W=1, 2020-12051ppm as H/W=2-4, and 51112-794026ppm as H/W=5-6. With a single elevated pollutant source, cases with viaducts experience significantly smaller pollutant exposures than cases without viaducts. Road barriers slightly increase pollutant exposure in near-road buildings with H/W=1 while reduce a little as H/W=3 and 5. Two-source cases can experience 2.60-5.52 times pollutant exposure as great as single-source cases.

The influence of street layouts and viaduct settings on daily carbon monoxide exposure and intake fraction in idealized urban canyons

Environmental concerns have been raised on the adverse health effects of vehicle emissions in micro-scale traffic-crowded street canyons, especially for pedestrians and residents living in near-road buildings. Viaduct design is sometimes used to improve transportation efficiency but possibly affects urban airflow and the resultant exposure risk, which have been rarely investigated so far. The personal intake fraction (P_IF) is defined as the average fraction of total emissions that is inhaled by each person of a population (1 ppm = 1 × 10^-6), and the daily carbon monoxide (CO) pollutant exposure (E_t) is estimated by multiplying the average concentration of a specific micro-environment within one day. As a novelty, by considering time activity patterns and breathing rates in various micro-environments for three age groups, this paper introduces IF and E_t into computational fluid dynamic (CFD) simulation to quantify the impacts of street layouts (street width/building height W/H = 1, 1.5, 2), source location, viaduct settings and noise barriers on the source-exposure correlation when realistic CO sources are defined. Narrower streets experience larger P_IF (1.51-5.21 ppm) and CO exposure, and leeward-side buildings always attain higher vehicular pollutant exposure than windward-side. Cases with a viaduct experience smaller P_IF (3.25-1.46 ppm) than cases without a viaduct (P_IF = 5.21-2.23 ppm) if the single ground-level CO source is elevated onto the viaduct. With two CO sources (both ground-level and viaduct-level), daily CO exposure rises 2.80-3.33 times but P_IF only change slightly. Noise barriers above a viaduct raise concentration between barriers, but slightly reduce vehicular exposure in near-road buildings. Because people spend most of their time indoors, vehicular pollutant exposure within near-road buildings can be 6-9 times that at pedestrian level. Although further studies are still required to provide practical guidelines, this paper provides effective methodologies to quantify the impacts of street/viaduct configurations on human exposure for urban design purpose.