Numerical modeling on air quality in an urban environment with changes of the aspect ratio and wind direction

Due to heavy traffic emissions within an urban environment, air quality during the last decade becomes worse year by year and hazard to public health. In the present work, numerical modeling of flow and dispersion of gaseous emissions from vehicle exhaust in a street canyon were investigated under changes of the aspect ratio and wind direction. The three-dimensional flow and dispersion of gaseous pollutants were modeled using a computational fluid dynamics (CFD) model which was numerically solved using Reynolds-averaged Navier–Stokes (RANS) equations. The diffusion flow field in the atmospheric boundary layer within the street canyon was studied for different aspect ratios (W/H?=?1/2, 3/4, and 1) and wind directions (θ?=?90°, 112.5°, 135°, and 157.5°). The numerical models were validated against wind tunnel results to optimize the turbulence model. The numerical results agreed well with the wind tunnel results. The simulation demonstrated that the minimum concentration at the human respiration height within the street canyon was on the windward side for aspect ratios W/H?=?1/2 and 1 and wind directions θ?=?112.5°, 135°, and 157.5°. The pollutant concentration level decreases as the wind direction and aspect ratio increase. The wind velocity and turbulence intensity increase as the aspect ratio and wind direction increase.     

Contribution of harbour activities and ship traffic to PM2.5, particle number concentrations and PAHs in a port city of the Mediterranean Sea (Italy)

In this work, an assessment of the impact of ship traffic and related harbour activities (loading/unloading of ships and hotelling in harbour) on PM 2.5 and particle number concentrations (PNC) separating the contribution associated to ship traffic from that of harbour-related activities is reported. Further, an assessment of the impact and environmental risks associated to polycyclic aromatic hydrocarbon (PAH) concentrations was performed. Results refer to the city of Brindisi (88,500 inhabitants) in the south-eastern part of Italy and its harbour (with yearly 9.5 Mt of goods, over 520,000 passengers and over 175,000 vehicles). PM2.5 and PNC concentrations show a clear daily pattern correlated with daily ship traffic pattern in the harbour. High temporal resolution measurements and correlations with wind direction were used to estimate the average direct contribution to measured concentrations of this source. The average relative contribution of ship traffic was 7.4 % (±0.5 %) for PM2.5 and 26 % (±1 %) for PNC. When the contribution associated to harbour-related activities is added, the percentages become 9.3 % (±0.5 %) for PM2.5 and 39 % (±1 %) for PNC. In the site analysed, air coming from the harbour/industrial sector was richer in PAHs (5.34 ng/m³) than air sampled from all directions (3.89 ng/m³). The major compounds were phenanthrene, fluoranthene and pyrene, but the congener profiles were different in the two direction sectors: air from the harbour/industrial sector was richer in phenanthrene and fluorene, which are the most abundant PAHs in ship emissions. Results showed that lighter PAHs are associated to the gas phase, while high molecular weight congeners are mostly present in the particulate phase. The impact on the site studied of the harbour/industrial source to PAHs was 56 % (range, 29–87 %).     

Predicting ozone levels

This paper presents a statistical model that is capable of predicting ozone levels from precursor concentrations and meteorological conditions during daylight hours in the Shuaiba Industrial Area (SIA) of Kuwait. The model has been developed from ambient air quality data that was recorded for one year starting from December 1994 using an air pollution mobile monitoring station. The functional relationship between ozone level and the various independent variables has been determined by using a stepwise multiple regression modelling procedure. The model contains two terms that describe the dependence of ozone on nitrogen oxides (NOx) and nonmethane hydrocarbon precursor concentrations, and other terms that relate to wind direction, wind speed, sulphur dioxide (SO₂) and solar energy. In the model, the levels of the precursors are inversely related to ozone concentration, whereas SO₂ concentration, wind speed and solar radiation are positively correlated. Typically, 63 % of the variation in ozone levels can be explained by the levels of NOx. The model is shown to be statistically significant and model predictions and experimental observations are shown to be consistent. A detailed analysis of the ozone-temperature relationship is also presented; at temperatures less than 27 °C there is a positive correlation between temperature and ozone concentration whereas at temperatures greater than 27 °C a negative correlation is seen. This is the first time a non-monotonic relationship between ozone levels and temperature has been reported and discussed.     

Wind Direction Bias in Generating Wind Roses and Conducting Sector-Based Air Dispersion Modeling

Abstract

Certain widely used wind rose programs and air dispersion models use an overly simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the directional bias that occurs from the aliasing that occurs when the sector widths used to report wind direction data are on the same order of magnitude, but not equal, to the sector widths used in the wind direction summaries. The directional bias issue arises when output products in 16 direction sectors (22.5° each) are produced from wind direction data reported in terms of 36 sectors (10° each). The result directional bias affects the results of simulations of air and surface concentrations using widely applied air dispersion models. Datasets or models with the directional bias discussed here give consistent positive biases (～30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all of the other sectors (around [?10%). Data summary and air dispersion programs providing outputs in direction sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the directional bias that can occur in transferring wind direction data between different sector widths.     

Near-road air pollution impacts of goods movement in communities adjacent to the Ports of Los Angeles and Long Beach

A mobile platform was outfitted with real-time instruments to spatially characterize pollution concentrations in communities adjacent to the Ports of Los Angeles and Long Beach, communities heavily impacted by emissions related to dieselized goods movement, with the highest localized air pollution impacts due to heavy-duty diesel trucks (HDDT). Measurements were conducted in the winter and summer of 2007 on fixed routes driven both morning and afternoon. Diesel-related pollutant concentrations such as black carbon, nitric oxide, ultrafine particles, and particle-bound polycyclic aromatic hydrocarbons were frequently elevated two to five times within 150 m downwind of freeways (compared to more than 150 m) and up to two times within 150 m downwind of arterial roads with significant amounts of diesel traffic. While wind direction was the dominant factor associated with downwind impacts, steady and consistent wind direction was not required to produce; high impacts were observed when a given area was downwind of a major roadway for any significant fraction of time. This suggests elevated pollution impacts downwind of freeways and of busy arterials are continuously occurring on one side of the road or the other, depending on wind direction. The diesel truck traffic in the area studied was high, with more than 2000 trucks per peak hour on the freeway and two- to six-hundred trucks per hour on the arterial roads studied. These results suggest that similarly-frequent impacts occur throughout urban areas in rough proportion to diesel truck traffic fractions. Thus, persons living or working near and downwind of busy roadways can have several-fold higher exposures to diesel vehicle-related pollution than would be predicted by ambient measurements in non-impacted locations.     

Characterization of Near-Road Pollutant Gradients Using Path-Integrated Optical Remote Sensing

Abstract

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R² = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

Characterization of near-road pollutant gradients using path-integrated optical remote sensing

Understanding motor vehicle emissions, near-roadway pollutant dispersion, and their potential impact to near-roadway populations is an area of growing environmental interest. As part of ongoing U.S. Environmental Protection Agency research in this area, a field study was conducted near Interstate 440 (I-440) in Raleigh, NC, in July and August of 2006. This paper presents a subset of measurements from the study focusing on nitric oxide (NO) concentrations near the roadway. Measurements of NO in this study were facilitated by the use of a novel path-integrated optical remote sensing technique called deep ultraviolet differential optical absorption spectroscopy (DUV-DOAS). This paper reviews the development and application of this measurement system. Time-resolved near-road NO concentrations are analyzed in conjunction with wind and traffic data to provide a picture of emissions and near-road dispersion for the study. Results show peak NO concentrations in the 150 ppb range during weekday morning rush hours with winds from the road accompanied by significantly lower afternoon and weekend concentrations. Traffic volume and wind direction are shown to be primary determinants of NO concentrations with turbulent diffusion and meandering accounting for significant near-road concentrations in off-wind conditions. The enhanced source capture performance of the open-path configuration allowed for robust comparisons of measured concentrations with a composite variable of traffic intensity coupled with wind transport (R2 = 0.84) as well as investigations on the influence of wind direction on NO dilution near the roadway. The benefits of path-integrated measurements for assessing line source impacts and evaluating models is presented. The advantages of NO as a tracer compound, compared with nitrogen dioxide, for investigations of mobile source emissions and initial dispersion under crosswind conditions are also discussed.     

C2–C5 Hydrocarbon measurements in the Netherlands 1981–1991

Measurements of C₂–C₅ hydrocarbons on an hourly basis at the TNO site in Delft from 1982 to 1984 and at Moerdijk over the period 1981–1991 are presented. In combination with meteorological data (wind direction and wind speed) the Delft and Moerdijk series are evaluated to identify source categories, annual variations, background concentrations and trends. The C₂–C₅ hydrocarbon concentrations at Delft and Moerdijk are determined mainly by emission characteristics and meteorological dispersion; the dominant sources are relatively nearby and atmospheric degradation is not of much importance. Under conditions of high wind speed the concentrations measured at Moerdijk in the marine sector are close to the Atlantic background concentrations in winter and somewhat above this in summer. The continental background concentrations are higher than the marine background concentrations by a factor of almost two. The annual variation of acetylene is more pronounced than that of the other hydrocarbons, most likely due to a different seasonal variation in acetylene emissions. The annual variation of propene is smoother, indicating stronger sources in summer than in winter. This feature of propene is observed in continental as well as in marine sectors. The observations show that at Moerdijk C₂–C₄ concentrations measured in Rijnmond sector have decreased considerably since the early 1980s, corresponding with changes in emissions in that area. Averaged over all wind directions the trend of all species is downward, but for acetylene the trend is significant at a 95% confidence interval. The acetylene concentrations show an annual downward trend of 3% during the 1980s, supporting other estimates of decreasing hydrocarbon emissions from traffic over this period at the same rate.     

Annual and seasonal variability of ambient aerosols over an urban region in western India

Annual and seasonal variabilities in source contribution to total suspended particles (TSP) measured over an urban location in western India, Ahmedabad between May 2000 and January 2003 are examined in this study. Positive matrix factorization (PMF) resolved six factors including airborne regional dust, calcium carbonate rich dust, biomass burning/vehicular emissions, secondary nitrate/sulfate, marine aerosol, and smelter. In this study, non-parametric statistical tests including the Kruskal–Wallis analysis of variance (K–W ANOVA) and Spearman rank correlation (ρ) test were used to assess the annual and seasonal variations in factor contributions, and the influence of meteorology on these contributions, respectively. None of the factor contributions exhibited annual variations except airborne regional dust, and biomass burning/vehicular emissions factors. All of the factors exhibited seasonal variations. Several factor monsoon (July–September) median concentrations were significantly different from one or more of the other season medians. In general, it appeared that meteorological factors played a role in establishing the seasonal behavior of factor contributions. Factor contributions exhibited low to moderate correlations with meteorological parameters such as temperature, relative humidity, wind direction, and wind speed. Amongst all of the relationships, marine aerosol factor was reasonably well correlated with relative humidity (ρ = 0.73) and wind direction (ρ = 0.73) during the pre-monsoon season (March–May). This observation suggests that the aerosol transported by moisture laden winds from the Arabian sea contribute to this factor. The airborne regional dust factor was also moderately correlated with wind speed (ρ = 0.70) during the post-monsoon season. This relationship indicates that high regional dust concentrations are favored by high wind speeds and the resultant increase in dispersion.     

Contribution of vehicular traffic and industrial facilities to PM10 concentrations in a suburban area of Caserta (Italy)

PM10 levels have been recorded in the suburban area of Caserta (Italy) from February to October 2012. The daily limit was exceeded in 13 % of the determinations, with no significant difference between weekdays and weekends. Benzo[a]pyrene concentrations were in the range 0.01–0.46 ng/m³, thus, never exceeding the National Standard. The B(a)P-eq was 0.20 ng/m³. PM10 peaks were associated with wind from east–northeast. The same was observed for Ca concentrations, whereas no relation with wind direction was observed for organic pollutants. The results point to a local limestone quarry and cement factory as the likely major source of PM10 pollution in the area investigated.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

Experimental investigation of the residence of contaminants in the wake of an obstacle under different stability conditions

The detrainment behaviour of contaminants in the wake of an isolated building was investigated in the field under atmospheric stability conditions ranging from very stable to very unstable. The model building used was a 2 m cube and two orientations were investigated, with the cube either normal or at 45° to the wind. Tracer gas was first entrained into the wake from a source located a short distance upwind of the cube, the gas being released continuously for a limited period in order to fill the wake. Thereafter, the source was switched off, and the concentration (measured using several fast-response gas detectors located in the wake) was observed to decay in an exponential manner. This procedure was repeated in a total of 118 experiments to provide confidence in statistics. The residence time (T_d), which is defined as the time it takes for the concentration to decay to 1/e of its original value, was measured. The decay duration (t), which is the time it takes for the gas to become fully detrained from the wake, was found to be greater in stable atmospheric conditions, mainly due to the lower wind speeds and higher concentrations observed under these conditions. However, the non-dimensional residence time (τ) was found to be independent of atmospheric stability. The values of τ for a cube normal (τ=6.2) or at 45° to the flow (τ=9.5) are in very good agreement with values calculated using empirical formulae derived from wind tunnel experiments.     

Roadside measurements of fine and ultrafine particles at a major road north of Gothenburg

Particle measurements were conducted at a road site 15 km north of the city of Gothenburg for 3 weeks in June 2000. The size distribution between 10 and 368 nm was measured continuously by using a differential mobility particle sizer (DMPS) system. PM_2.5 was sampled on a daily basis with subsequent elemental analysis using EDXRF-spectroscopy. The road is a straight four-lane road with a speed limit of 90 kph. The road passing the site is flat with no elevations where the vehicles run on a steady workload and with constant speed. The traffic intensity is about 20,000 cars per workday and 13,000 vehicles per day during weekends. The diesel fuel used in Sweden is low in sulphur content (<10 ppm) and therefore the diesel vehicles passing the site contribute less to particle emissions in comparison with other studies. A correlation between PM_2.5 and accumulation mode particles (100–368 nm) was observed. However, no significant correlation was found between number concentrations of ultrafine particles (10–100 nm) and PM_2.5 or the accumulation mode number concentration. The particle distribution between 10 and 368 nm showed great dependency on wind speed and wind direction, where the wind speed was the dominant factor for ultrafine (10–100 nm) particle concentrations. The difference in traffic intensity between workday and weekend together with wind data made it possible to single out the traffic contribution to particle emissions and measure the size distribution. The results presented in combination with previous studies show that both PM_2.5 and the mass of accumulation mode particles are bad estimates for ultrafine particles.     

Effect of urban morphology on wind condition in idealized city models

Wind conditions in urban environments are important for a number of reasons. They can serve to transport air pollutants out of the urban environment and to moderate urban microclimatic conditions if satisfactory, yet can compromise pedestrian comfort and safety if not. We aim to study experimentally and numerically the effects of urban morphology (e.g., overall city form (skyline), street orientation, and street configuration) on wind conditions in cities. This report considers our initial investigations of two idealized city forms that are coincidentally similar to ancient Roman cities that were organized on one or two primary streets – a main north–south street, the cardus maximus, and a secondary east–west street, the decumanus maximus – and contained within a well-defined perimeter.We first consider round and square city models with one main street set parallel to the approaching wind and a secondary street producing an intersection at city centre. Not surprisingly, wind conditions in the two city models are dissimilar due to their shape differences. We then consider a long rectangular city model with a fully developed steady flow region along the main street. If the main street of the round city model is narrow, the parallel approaching wind cannot blow through the entire street and a penetrating inflow exists at the leeward opening. For the round city model with two crossing streets, a slightly non-parallel wind to the main street generates a stronger wind level in the entire street volume.     

Observations of winds above and below a forest canopy located near a clearing

Measurements of wind movements have been made within and above a forest canopy located near a 0.5 km² clearing. They showed the existence of complex wind systems characterized by strong horizontal jets of air and large vertical velocities beneath the canopy during unstable atmospheric conditions. Under stable situations wind flows seemed to be less complex with both horizontal and vertical winds being greater above the canopy than below.     

Statistical and diagnostic evaluation of a new-generation urban dispersion modelling system against an extensive dataset in the Helsinki area

We have developed a modelling system for predicting the traffic volumes, emissions from stationary and vehicular sources, and atmospheric dispersion of pollution in an urban area. This paper describes a comparison of the NO_x and NO₂ concentrations predicted using this modelling system with the results of an urban air quality monitoring network. We performed a statistical analysis to determine the agreement between predicted and measured hourly time series of concentrations at four permanently located and three mobile monitoring stations in the Helsinki Metropolitan Area in 1996–1997 (at a total of ten urban and suburban measurement locations). At the stations considered, the so-called index of agreement values of the predicted and measured time series of the NO₂ concentrations vary between 0.65 and 0.82, while the fractional bias values range from −0.29 to +0.26. In comparison with corresponding results presented in the literature, the agreement between the measured and predicted datasets is good, as indicated by these statistical parameters. The seasonal variations of the NO₂ concentrations were analysed in terms of the relevant meteorological parameters. We also analysed the difference between model predictions and measured data diagnostically, in terms of meteorological parameters, including wind speed and direction (the latter separately for two wind speed classes), atmospheric stability and ambient temperature, at two monitoring stations in central Helsinki. The modelling system tends to overpredict the measured NO₂ concentrations both at the highest (u⩾6 m s⁻¹) and at the lowest wind speeds (u<2 m s⁻¹). For higher wind speeds, the modelling system overpredicts the measured NO₂ concentrations in certain wind direction intervals; specific ranges were found for both monitoring stations considered. The modelling system tends to underpredict the measured concentrations in convective atmospheric conditions, and overpredict in stable conditions. The possible physico-chemical reasons for these differences are discussed.     

Treatment of reactive dyes and textile finishing wastewater using Fenton's oxidation for reuse

Fenton's oxidation (FO) was used to decolourise and degrade some reactive dyes (Remazol Black 5, Remazol Red, Remazol Blue, Remazol Yellow) and raw textile finishing industry effluents (S1, S2, S3) containing mainly reactive dyes. The operational conditions for pH varied between 2.5 and 4.0 while temperature ranged from 30°C to 50°C. The concentrations of FeSO₄ and H₂O₂ varied to a wide range (200–600 mg/l of FeSO₄, 300–1000 mg/l of H₂O₂) depending on the type of the dyes and their mixture and textile additives used in the process. FO is highly effective for colour removal (>99%) for reactive dyes and (87–94%) for textile finishing wastewater. It can be applied as a pretreatment and the remaining total dissolved solids (TDS) can be removed by an additional advanced process, e.g. membrane process.     

Source apportionment and location by selective wind sampling and Positive Matrix Factorization

In order to determine the pollution sources in a suburban area and identify the main direction of their origin, PM_2.5 was collected with samplers coupled with a wind select sensor and then subjected to Positive Matrix Factorization (PMF) analysis. In each sample, soluble ions, organic carbon, elemental carbon, levoglucosan, metals, and Polycyclic Aromatic Hydrocarbons (PAHs) were determined. PMF results identified six main sources affecting the area: natural gas home appliances, motor vehicles, regional transport, biomass combustion, manufacturing activities, and secondary aerosol. The connection of factor temporal trends with other parameters (i.e., temperature, PM_2.5 concentration, and photochemical processes) confirms factor attributions. PMF analysis indicated that the main source of PM_2.5 in the area is secondary aerosol. This should be mainly due to regional contributions, owing to both the secondary nature of the source itself and the higher concentration registered in inland air masses. The motor vehicle emission source contribution is also important. This source likely has a prevalent local origin. The most toxic determined components, i.e., PAHs, Cd, Pb, and Ni, are mainly due to vehicular traffic. Even if this is not the main source in the study area, it is the one of greatest concern. The application of PMF analysis to PM_2.5 collected with this new sampling technique made it possible to obtain more detailed results on the sources affecting the area compared to a classical PMF analysis.     

Air pollutant concentrations near three Texas roadways,Part I: Ultrafine particles

Vehicular emitted air pollutant concentrations were studied near three types of roadways in Austin, Texas: (1) State Highway 71 (SH-71), a heavily traveled arterial highway dominated by passenger vehicles; (2) Interstate 35 (I-35), a limited access highway north of Austin in Georgetown; and (3) Farm to Market Road 973 (FM-973), a heavily traveled surface roadway dominated by truck traffic. Air pollutants examined include carbon monoxide (CO), oxides of nitrogen (NO_x), and carbonyl species in the gas-phase. In the particle phase, ultrafine particle (UFP) concentrations (diameter < 100 nm), fine particulate matter (PM_2.5, diameter < 2.5 μm) mass and carbon content and several particle-bound organics were examined. All roadways had an upwind stationary sampling location, one or two fixed downwind sample locations and a mobile monitoring platform that characterized pollutant concentrations fall-off with increased distance from the roadways. Data reported in this paper focus on UFP while other pollutants and near-roadway chemical processes are examined in a companion paper. Traffic volume, especially heavy-duty traffic, wind speed, and proximity to the road were found to be the most important factors determining UFP concentrations near the roadways. Since wind directions were not consistent during the sampling periods, distances along wind trajectories from the roadway to the sampling points were used to study the decay characteristics of UFPs. Under perpendicular wind conditions, for all studied roadway types, particle number concentrations increased dramatically moving from the upwind side to the downwind side. The elevated particle number concentrations decay exponentially with increasing distances from the roadway with sharp concentration gradients observed within 100–150 m, similar to previously reported studies. A single exponential decay curve was found to fit the data collected from all three roadways very well under perpendicular wind conditions. No consistent pattern was observed for UFPs under parallel wind conditions. However, regardless of wind conditions, particle concentrations returned to background levels within a few hundred meters of the roadway. Within measured UFP size ranges, smaller particles (6–25 nm) decayed faster than larger ones (100–300 nm). Similar decay rates were observed among UFP number, surface, and volume.     

Minimizing the effect of automotive pollution in urban geometry using mathematical optimization

One of the factors that needs to be considered during the layout of new urban geometry (e.g. street direction, spacing and width, building height restrictions) is the effect of the air pollution associated with the automotive transport that would use routes in this urban area. Although the pollution is generated at street level, its effect can be widespread due to interaction of the pollutant dispersion and diffusion with the wind speed and direction. In order to study the effect of a new urban geometry on the pollutant levels and dispersion, a very time-consuming experimental or parametric numerical study would have to be performed. This paper proposes an alternative approach, that of combining mathematical optimization with the techniques of computational fluid dynamics (CFD). In essence, the meteorological information as represented by a wind rose (wind speed and direction), is used to calculate pollutant levels as a function of urban geometry variables: street canyon depth and street canyon width. The pollutant source specified in conjunction with a traffic scenario with CO is used as pollutant. The main aim of the study is to be able to suggest the most beneficial configuration of an idealized urban geometry that minimizes the peak pollutant levels due to assumed traffic distributions. This study uses two mathematical optimization methods. The first method is implemented through a successive maximization–minimization approach, while the second method determines the location of saddle points of the pollutant level, considered as a function of urban geometry and wind rose. Locally, a saddle point gives the best urban geometry for the worst meteorological scenario. The commercial CFD code, STAR-CD, is coupled with a version of the DYNAMIC-Q optimization algorithm of Snyman, first to successively locate maxima and minima in a min–max approach; and then to locate saddle points. It is shown that the saddle-point method is more cost-effective. The methodology presented in this paper can readily be extended to optimize traffic patterns for existing geometry or in the development of geometry modification for pollution control or toxic releases.