CFD modelling of air quality in Pamplona City (Spain): Assessment, stations spatial representativeness and health impacts valuation

Impact of single and combined local air pollution mitigation measures in an urban environment

Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.

Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp

In the framework of the Forum for Air Quality Modelling in Europe (FAIRMODE), a modelling intercomparison exercise for computing NO2 long-term average concentrations in urban districts with a very high spatial resolution was carried out. This exercise was undertaken for a district of Antwerp (Belgium). Air quality data includes data recorded in air quality monitoring stations and 73 passive samplers deployed during one-month period in 2016. The modelling domain was 800 × 800 m2. Nine modelling teams participated in this exercise providing results from fifteen different modelling applications based on different kinds of model approaches (CFD - Computational Fluid Dynamics-, Lagrangian, Gaussian, and Artificial Intelligence). Some approaches consisted of models running the complete one-month period on an hourly basis, but most others used a scenario approach, which relies on simulations of scenarios representative of wind conditions combined with post-processing to retrieve a one-month average of NO2 concentrations. The objective of this study is to evaluate what type of modelling system is better suited to get a good estimate of long-term averages in complex urban districts. This is very important for air quality assessment under the European ambient air quality directives. The time evolution of NO2 hourly concentrations during a day of relative high pollution was rather well estimated by all models. Relative to high resolution spatial distribution of one-month NO2 averaged concentrations, Gaussian models were not able to give detailed information, unless they include building data and street-canyon parameterizations. The models that account for complex urban geometries (i.e. CFD, Lagrangian, and AI models) appear to provide better estimates of the spatial distribution of one-month NO2 averages concentrations in the urban canopy. Approaches based on steady CFD-RANS (Reynolds Averaged Navier Stokes) model simulations of meteorological scenarios seem to provide good results with similar quality to those obtained with an unsteady one-month period CFD-RANS simulations.

Indoor particle dispersion due to hand dryer in public washroom: an in silico study

Hand dryer in public washroom has been reported likely to be a reservoir of drug-resistant bacteria. When a hand dryer being used, the high-velocity air jet from the dryer outlet can carry aerosol particles to hand surfaces, the user, and indoor space. This in silico study considered the effect of different airflow speed of hand dryers on the dispersion of particles in different diameters with and without the user. The aim of this study was to apply the computational fluid dynamics (CFD) method based on the discrete phase model to investigate the trajectory of indoor particles from the hand dryer in public washroom. The CFD results showed that, when the user was using the hand dryer, 42.3% of the particles were distributed on the wall against the user, and 31.6% were distributed on the user's body, including their hands. When no one was standing in front of the hand dryer, 87.6% of the particles fell on the ground. The blocking of user's hand dispersed the particles to a wide range, particularly for the larger diameter particles which were scattered on the user's body or on the ground. In addition, the dispersion proportion of particles did not vary with the speed of airflow, but the area of particles distribution became larger as the speed increased. Our findings suggest that the contamination of the indoor environment caused by the hand dryer could not be ignored, incorporating filters into hand dryers is essential. Furthermore, our work offers valuable insights for optimizing the design of hand dryers.

Impact of Different Combinations of Green Infrastructure Elements on Traffic-Related Pollutant Concentrations in Urban Areas

Urban air quality is a major problem for human health and green infrastructure (GI) is one of the potential mitigation measures used. However, the optimum GI design is still unclear. The purpose of this study is to provide some recommendation that could help in the design of the GI (mainly, the selection of locations and characteristics of trees and hedgerows). Aerodynamic and deposition effects of each vegetation element of different GI scenarios are investigated. Computational fluid dynamics (CFD) simulations of a wide set of GI scenarios in an idealized three-dimensional urban environment are performed. In conclusion, it was found that trees in the middle of the avenue (median strip) reduce street ventilation, and traffic-related pollutant concentrations increase, in particular for streets parallel to the wind. Trees in the sidewalks act as a barrier for pollutants emitted outside, specifically for a 45° wind direction. Regarding hedgerows, the most important effect on air quality is deposition and the effects of green walls and green roofs are limited to their proximity to the building surfaces.

Spatiotemporal representativeness of air pollution monitoring in Dublin, Ireland

The importance of selecting appropriate air pollution monitoring sites in a city is vital for accurately reporting air quality, enhancing the quality of high-resolution modelling and informing policy to implement measures to deliver cleaner air in the urban environment. COVID-19 restrictions impacted air quality in urban centres worldwide as reduced mobility led to changes in traffic-related air pollution (TRAP). As such, it offered a unique dataset to examine the spatial and temporal variations in air quality between monitoring stations in Dublin, Ireland. Firstly, an analysis of mobility data showed reductions across almost all sectors after COVID-19 restrictions came into place, which was expected to lower TRAP. In addition, similar changes in air quality were evident to other cities around the world: reductions in fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations and an increase in ozone (O₃) concentrations. Average daily and diurnal concentrations for these three pollutants presented more statistically significant spatial and temporal changes during COVID-19 restrictions at monitoring sites with urban or traffic classifications than suburban background sites. Furthermore, substantial reductions in the range of average hourly pollutant concentrations were observed, 79% for PM_2.5 and 75% for NO₂, with a modest 24% reduction for O₃. Correlation analysis of air pollution between monitoring sites and years demonstrated an improvement in the R² for NO₂ concentrations only, suggesting that spatiotemporal homogeneity was most notable for this TRAP due to mobility restrictions during COVID-19. The spatiotemporal representativeness of monitoring stations across the city will change with greener transport, and air quality during COVID-19 can provide a benchmark to support the introduction of new policies for cleaner air.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

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

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

Estimates of population exposure to atmospheric pollution and health-related externalities in a real city: The impact of spatial resolution on the accuracy of results

Health impacts of atmospheric pollution is an important issue in urban environments. Its magnitude depends on population exposure which have been frequently estimated by considering different approaches relating pollutant concentration and population exposed to it. However, the uncertainties due to the spatial resolution of the model used to estimate the pollutant concentration or due to the lack of representativeness of urban air quality monitoring station (AQMS) have not been evaluated in detail. In this context, NO₂ annual average concentration at pedestrian level in the whole city of Pamplona (Spain) modelled at high spatial resolution (~1 m) by Computational Fluid Dynamic (CFD) simulations is used to estimate the total population exposure and health-related externalities by using different approaches. Air pollutant concentration and population are aggregated at different spatial resolutions ranging from a horizontal grid cell size of 100 m × 100 m to a coarser resolution where the whole city is covered by only one cell (6 km × 5 km). In addition, concentrations at AQMS locations are also extracted to assess the representativeness of those AQMS. The case with a spatial resolution of 100 m × 100 m for both pollutant-concentration distribution and population data is used as a reference (Base case) and compared with those obtained with the other approaches. This study indicates that the spatial resolution of concentration and population distribution in the city should be 1 km × 1 km or finer to obtain appropriate estimates of total population exposure (underestimations <13%) and health-related externalities (underestimations <37%). For the cases with coarser resolutions, a strong underestimation of total population exposure (>31%) and health-related externalities (>76%) was found. On the other hand, the use of AQMS concentrations can induce important errors due to the limited spatial representativeness, in particular in terms of population exposure.

Impact of natural ventilation on exposure to SARS-CoV 2 in indoor/semi-indoor terraces using CO2 concentrations as a proxy

Nowadays, it is necessary a better airborne transmission understanding of respiratory diseases in shared indoor and semi-indoor environments with natural ventilation in order to adopt effective people's health protection measures. The aim of this work is to evaluate the relative exposure to SARS-CoV 2 in a set of virtual scenarios representing enclosed and semi-enclosed terraces under different outdoor meteorological conditions. For this purpose, indoor CO₂ concentration is used as a proxy for the risk assessment. Airflow and people exhaled CO₂ in different scenarios are simulated through Computational Fluid Dynamics (CFD) modelling with Unsteady Reynolds-Averaged Navier-Stokes (URANS) approach. Both spatial average concentrations and local concentrations are analyzed. In general, spatial average concentrations decrease as ventilation increases, however, depending on the people arrangement inside the terrace, spatial average concentrations and local concentrations can be very different. Therefore, for assessing the relative exposure to SARS-CoV 2 it is necessary to consider the indoor flow patterns between infectors and susceptibles. This research provides detailed information about CO₂ dispersion in enclosed/semi-enclosed scenarios, which can be very useful for reducing the transmission risk through better natural ventilation designs and improving the classic risk models since it allows to check their hypotheses in real-world scenarios. Although CFD ventilation studies in indoor/semi-indoor environments have been already addressed in the literature, this research is focused on restaurant terraces, scenarios scarcely investigated. Likewise, one of the novelties of this study is to take into account the outdoor meteorological conditions to appropriately simulate natural ventilation.

High Spatial Resolution Assessment of the Effect of the Spanish National Air Pollution Control Programme on Street-Level NO2 Concentrations in Three Neighborhoods of Madrid (Spain) Using Mesoscale and CFD Modelling

Current European legislation aims to reduce the air pollutants emitted by European countries in the coming years. In this context, this article studies the effects on air quality of the measures considered for 2030 in the Spanish National Air Pollution Control Programme (NAPCP). Three different emission scenarios are investigated: a scenario with the emissions in 2016 and two other scenarios, one with existing measures in the current legislation (WEM2030) and another one considering the additional measures of NAPCP (WAM2030). Previous studies have addressed this issue at a national level, but this study assesses the impact at the street scale in three neighborhoods in Madrid, Spain. NO2 concentrations are modelled at high spatial resolution by means of a methodology based on Computational Fluid Dynamic (CFD) simulations driven by mesoscale meteorological and air quality modelling. Spatial averages of annual mean NO2 concentrations are only estimated to be below 40 µg/m3 in all three neighborhoods for the WAM2030 emission scenarios. However, for two of the three neighborhoods, there are still zones (4–12% of the study areas) where the annual concentration is higher than 40 µg/m3. This highlights the importance of considering microscale simulations to assess the impacts of emission reduction measures on urban air quality.

How to compute long-term averages for air quality assessment at urban areas?

This paper proposes two innovative time-effective approaches to retrieve annual averaged concentrations for air quality assessment in the framework of the AQD. In addition, a traditional method (M1) was applied through numerical simulations for an entire year on an hourly basis to compare the performance of the proposed approaches. The first time-effective approach (M2) is based on the calculation of pollutant concentrations for the full year on an hourly basis through the combination of a set of numerical simulations for 4 typical days weighted by hourly factors obtained from air quality monitoring data. While the second time-effective approach (M3) considers the numerical simulation of pollutant concentrations for a set of typical meteorological conditions. For all the methods, air quality simulations were performed with the second-generation Gaussian model URBAIR. The three methods are applied over two distinct European urban areas, the Aveiro region in Portugal and Bristol in the United Kingdom, for the simulation of NO₂ and PM10 annual concentrations. The main results highlight an underestimation of the NO₂ annual concentrations by M2 and an overestimation of those concentrations by M3 for the Aveiro region, when compared to M1 as the reference method. While, for Bristol the main differences between methods were found for NO₂ concentrations when using M3. M2 underestimates PM10 annual concentrations in the Aveiro Region, while M3 points out underestimation or overestimation of those concentrations for distinct areas of the domain. This study aims to foster the knowledge on air quality assessment under the European policy context, supporting air quality management and urban planning. The innovative nature of this study relies on the proposed time-effective tools, suitable for the fast simulation of complex urban areas applying high spatial resolution. Additionally, these modelling tools may provide key information on air quality to population, particularly where it is not readily available.

Wind Environment Simulation Accuracy in Traditional Villages with Complex Layouts Based on CFD

Using wind speed, wind direction, and turbulence intensity values as evaluation indicators, the ventilation performance of villages with complex building layouts was studied. We used the SKE, RNG, and RKE solvers in CFD-3D steady-state Reynolds-averaged Navier–Stokes (RANS) to simulate the wind environment of a village. The findings show that for the simulation of rural wind environments with complex building layouts, steady-state simulation solvers need to be evaluated in detail to verify their accuracy. In this study, a village with a complex architectural layout in Southern Shaanxi, China, was taken as the research object, and three steady-state simulation solvers were used to evaluate the ventilation performance of the village. The simulated data were compared with the measured data to find the most suitable solver for this kind of village wind environment simulation. The results show that for the simulation of the village wind environment with a complex building layout, the RNG simulation results have the lowest reliability among the three steady-state solvers. The reliability of wind speed distribution and turbulence intensity distribution are 0.7881 and 0.2473, respectively. However, the wind speed and turbulence intensity values obtained by the SKE solver are the closest to the measured values, which are 0.8625 and 0.9088, respectively. Therefore, for villages with complex building layouts, the SKE solver should be the first choice for simulating wind environment distribution. When using the RNG solver, the overall turbulence intensity value obtained is higher than the measured value. The average deviation between the simulated data and SKE and RKE at a height of 1.7 m is 42.61%. The main reason for this is that RNG overestimates the vortices and underestimates the airflow rate in the building intervals.

The assessment of two different pollutants dispersion from a coal-fired power plant for various thermal regimes

In this study, numerical simulations of the movement and emissions dispersion of two pollutants (sulfur dioxide(SO₂) and carbon dioxide(CO₂)) into the atmospheric boundary layer were considered under natural atmospheric conditions. To test the numerical algorithm and to select the optimal turbulent model, the test problem was solved numerically. The obtained computational data were compared with measurement data and values from the computation of other authors and the SST k-omega model illustrated the closest values to the data from the experiment, this is achieved by modifying the boundary condition for turbulent kinetic energy. The tested computational algorithm was used to characterize the emissions process of two pollutants from two chimneys of the Ekibastuz SDPP and the distribution of CO₂ and SO₂ in the air flow field in natural air condition. For this task, four various velocity variations were considered, as well as several various thermal variations (temperature inversion, constant temperature and decreasing temperature by the height). From the obtained computational results, it should be noticed that different environmental temperature conditions extremely impact the distribution of pollutants CO₂ and SO₂ in the atmospheric surface layer, so at constant temperature conditions, the species for all velocity variations have nearly identical species profile.

A proposed population-health based metric for evaluating representativeness of air quality monitoring in cities: Using Hong Kong as a demonstration

City air quality monitoring (AQM) network are typically sparsely distributed due to high operation costs. It is of the question of how well it can reflect public health risks to air pollution given the diversity and heterogeneity in pollution, and spatial variations in population density. Combing high-resolution air quality model, spatial population distribution and health risk factors, we proposed a population-health based metric for AQM representativeness. This metric was demonstrated in Hong Kong using hourly modelling data of PM10, PM2.5, NO2 and O3 in 2019 with grid cells of 45m * 48m. Individual and total hospital admission risks (%AR) of these pollutants were calculated for each cell, and compared with those calculated at 16 monitoring sites using the similarity frequency (SF) method. AQM Representativeness was evaluated by SF and a population-health based network representation index (PHNI), which is population-weighted SF over the study-domain. The representativeness varies substantially among sites as well as between population- and area-based evaluation methods, reflecting heterogeneity in pollution and population. The current AQM network reflects population health risks well for PM10 (PHNI = 0.87) and PM2.5 (PHNI = 0.82), but is less able to represent risks for NO2 (PHNI = 0.59) and O3 (PHNI = 0.78). Strong seasonal variability in PHNI was found for PM, increasing by >11% during autumn and winter compared to summer due to regional transport. NO2 is better represented in urban than rural, reflecting the heterogeneity of urban traffic pollution. Combined health risk (%ARtotal) is well represented by the current AQM network (PHNI = 1), which is more homogenous due to the dominance and anti-correlation of NO2 and O3 related %AR. The proposed PHNI metric is useful to compare the health risk representativeness of AQM for individual and multiple pollutants and can be used to compare the effectiveness of AQM across cities.

Estimates of pedestrian exposure to atmospheric pollution using high-resolution modelling in a real traffic hot-spot

Atmospheric pollution is a very relevant risk for the human health, in particular in urban environments, where most people lives and high levels of pollution are found. Population exposure is traditionally estimated through concentration recorded at air quality monitoring stations (AQMS) or modelled at a spatial resolution of the order of 1 km². However, these methodologies have limitations in urban areas where strong gradients of concentration, even in the same street, exist. In addition, the movements of pedestrians make difficult to compute reliable estimates of pollutant concentration to which people are exposed to. In this context, the main objective of this study is to estimate the exposure of pedestrians to ambient nitrogen oxides (NOx) concentrations with high spatial resolution in a real urban traffic hot-spot under different methodologies. To achieve this objective, a novel methodology which combines high-resolution NOx concentrations from computational fluid dynamic (CFD) simulations with the pedestrian flows obtained by pedestrian mobility microsimulations is applied to an urban area of Madrid, Spain. High-resolution maps show pedestrian exposure peaks, at bus stops and crosswalks, that cannot be captured by the simpler methods based on spatial average concentration (SAC) or concentration measured in an AQMS. Total daily exposure obtained is 1.19 · 10⁹ person s μg m^-3, while SAC and AQMS concentration methods yielded 9-23% and 30-40% lower values. In conclusion, the proposed methodology allows to determine the areas with higher exposure in order to design local strategies to reduce the impact on human health. In addition, from a more general point of view, the total exposure in the studied area is better estimated by using spatial average concentration than through concentration recorded by AQMS. The assessment of the spatial representative of AQMS becomes necessary to use AQMS concentration to evaluate air quality and population exposure of an urban area.

Spatio-Temporal Representativeness of Air Quality Monitoring Stations in Mexico City: Implications for Public Health

Assessment of the air quality in metropolitan areas is a major challenge in environmental sciences. Issues related include the distribution of monitoring stations, their spatial range, or missing information. In Mexico City, stations have been located spanning the entire Metropolitan zone for pollutants, such as CO, NO2, O3, SO2, PM2.5, PM10, NO, NO x , and PM CO . A fundamental question is whether the number and location of such stations are adequate to optimally cover the city. By analyzing spatio-temporal correlations for pollutant measurements, we evaluated the distribution and performance of monitoring stations in Mexico City from 2009 to 2018. Based on our analysis, air quality evaluation of those contaminants is adequate to cover the 16 boroughs of Mexico City, with the exception of SO2, since its spatial range is shorter than the one needed to cover the whole surface of the city. We observed that NO and NO x concentrations must be taken into account since their long-range dispersion may have relevant consequences for public health. With this approach, we may be able to propose policy based on systematic criteria to locate new monitoring stations.

Benefit Analysis of the 1st Spanish Air Pollution Control Programme on Health Impacts and Associated Externalities

This paper aims to provide scientific support for decision-making in the field of improving air quality by evaluating pollution reduction measures included in the current Spanish policy framework of the 1st National Air Pollution Control Programme (NAPCP). First, the health impacts of air quality are estimated by using the concentrations estimated by multiscale air quality modeling and the recommended concentration–response functions (CRF), specifically as a result of exposure to particulate matter (PM), nitrogen dioxide (NO2), and ozone (O3). Second, the associated external costs are calculated by monetization techniques. Two scenarios are analyzed: a package including existing measures (WM2030) and a package with additional measures (WAM2030). Compared with the baseline scenario, an improvement was found in the health effects of NO2, PM10, and PM2.5, while for O3 there was a slight worsening, mainly due to the increase in the O3 metric used (SOMO35), which increases over some urban areas. Despite this, the monetary valuation of the total effects on health as a whole shows external benefits due to the adoption of measures (WM2030), compared with the reference scenario (no measures) of more than € 17.5 billion and, when considering the additional measures (WAM2030), benefits of about € 58.1 billion.

CFD study and experimental validation of low liquid-loading flow assurance in oil and gas transport: studying the effect of fluid properties and operating conditions on flow variables

Low liquid-loading flow frequently occurs during the transport of gas products in various industries, such as in the Oil & Gas, the Food, and the Pharmaceutical Industries. Even small amounts of liquid can have a significant effect on the flow conditions inside the pipeline, such as increased pressure loss, pipe wall stresses and corrosion, and liquid holdup along the pipeline. However, most studies that analyze this type of flow only use atmospheric pressures and horizontal 1-in or 2-in pipes, which do not accurately represent the range of operating conditions present in industrial applications. Therefore, this study focused on modeling low liquid-loading flow in medium-sized (6–10 in) pipes, using CFD simulations and experimental data from the University of Tulsa, and then applying it to real operating conditions from a Colombian gas pipeline. An acceptable difference was observed between experimental and CFD data, both for the liquid holdup (18%) and for the pressure drop (12%). Variables like pressure drop and wall shear stress increase with phase velocity, operating pressure, and pipe inclination. Liquid holdup increases with liquid velocity but decreases with all other factors. The relation of flow variables with phase velocities is of particular interest: Doubling the gas velocity decreased holdup 70% and increased pressure drop tenfold. On the other hand, the presence of the liquid phase seems to be more influential on process variables than its exact flowrate; the introduction of the liquid phase to a single-phase gas causes an increase in pressure loss by a factor of three, but doubling the liquid velocity only increases the pressure loss by a further 30%.

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.

Modeling Emission Flow Pattern of a Single Cruising Vehicle on Urban Streets with CFD Simulation and Wind Tunnel Validation

Transportation has become one of the primary sources of urban atmospheric pollutants and it causes severe diseases among city residents. This study focuses on assessing the pollutant dispersion pattern using computational fluid dynamics (CFD) numerical simulation, with the effect and results validated by the results from wind tunnel experiments. First, the wind tunnel experiment was carefully designed to preliminarily assess the flow pattern of vehicle emissions. Next, the spatiotemporal distribution of pollutant concentrations around the motor vehicle was modeled using a CFD numerical simulation. The pollutant concentration contours indicated that the diffusion process of carbon monoxide mainly occurred in the range of 0-2 m above the ground. Meanwhile, to verify the correctness of the CFD simulation, pressure distributions of seven selected points that were perpendicular along the midline of the vehicle surface were obtained from both the wind tunnel experiment and the CFD numerical simulation. The Pearson correlation coefficient between the numerical simulation and the wind tunnel measurement was 0.98, indicating a strong positive correlation. Therefore, the distribution trend of all pressure coefficients in the numerical simulation was considered to be consistent with those from the measurements. The findings of this study could shed light on the concentration distribution of platoon-based vehicles and the future application of CFD simulations to estimate the concentration of pollutants along urban street canyons.

A CFD analysis of the pollutant dispersion from cooling towers with various configurations in the lower region of atmospheric boundary layer

The mixing and merging of buoyant plumes originating from multiple small cooling towers into the atmosphere is numerically investigated. The effects of different arrangements of cooling towers as well as outlet geometries on the mixing of the plumes are examined. The side by side and tandem arrangements of two sources and also two types of multi-flue cooling towers are considered. The various ways by which the counter rotating vortex pair, as the dominant mechanism, affect the flow pattern in each aforementioned configuration are investigated. For tandem arrangement, far from sources, the outlet flow of the downstream cooling tower surrounds the plumes originating from the upstream cooling tower and in the region near the cooling towers, the pollutants are mostly originated from the upstream cooling tower. Maximum pollutant concentrations at distances 10 and 40 times the diameter downstream of the leading cooling tower increase by 67% and 29% with respect to those of a single cooling tower, respectively. For the side by side arrangement, the counter rotating vortices are stretched due to the large low pressure area created downstream of the cooling towers. Mixing of the plumes with the surrounding air is reduced as a result of contraction of vortices. Maximum contaminant concentrations at distances 10 and 40 times the diameter downstream of the cooling towers increase by 29% and 41% with respect to those of a single tower, respectively. Finally, the differences between flow fields formed around diamond and square configurations of multi-flue cooling towers are extensively discussed.

On the Impact of Trees on Ventilation in a Real Street in Pamplona, Spain

This paper is devoted to the quantification of changes in ventilation of a real neighborhood located in Pamplona, Spain, due to the presence of street trees Pollutant dispersion in this urban zone was previously studied by means of computational fluid dynamic (CFD) simulations. In the present work, that research is extended to analyze the ventilation in the whole neighborhood and in a tree-free street. Several scenarios are investigated including new trees in the tree-free street, and different leaf area density (LAD) in the whole neighborhood. Changes between the scenarios are evaluated through changes in average concentration, wind speed, flow rates and total pollutant fluxes. Additionally, wind flow patterns and the vertical profiles of flow properties (e.g., wind velocity, turbulent kinetic energy) and concentration, horizontally-averaged over one particular street, are analyzed. The approach-flow direction is almost perpendicular to the street under study (prevailing wind direction is only deviated 4º from the perpendicular direction). For these conditions, as LAD increases, average concentration in the whole neighborhood increases due to the decrease of wind speed. On the other hand, the inclusion of trees in the street produces an increase of averaged pollutant concentration only within this street, in particular for the scenario with the highest LAD value. In fact, the new trees in the street analyzed with the highest LAD value notably change the ventilation producing an increase of total pollutant fluxes inward the street. Additionally, pollutant dispersion within the street is also influenced by the reduction of the wind velocity along the street axis and the decrease of turbulent kinetic energy within the vegetation canopy caused by the new trees. Therefore, the inclusion of new trees in a tree-free street should be done by considering ventilation changes and traffic emissions should be consequently controlled in order to keep pollutant concentration within healthy levels.