A study of pollutant dispersion near highways

As a part of a major roadway dispersion project undertaken by the New York State Department of Environmental Conservation, several tracer release experiments were conducted on an open, at-grade highway site. The observed concentration profiles indicate that the tracer concentration decreases with increasing distance from the roadway more rapidly for parallel wind-road orientation than for perpendicular wind-road orientation. However, the decrease of concentration with height on the tower at the nearest, downwind roadside receptor is slow for parallel case as compared to perpendicular case.Four Gaussian dispersion models (HIWAY, GM, CALINE-2, AIRPOL-4) and four numerical models (DANARD, MROAD 2, RAGLAND, ROADS) are used to predict the tracer gas concentrations. Of the models tested, GM and HIWAY perform well compared to other Gaussian models. The numerical models performed about the same as the above two Gaussian models. The GM model provides a better simulation by far for parallel wind cases than any of the other models tested.The computed wind flow patterns indicate upward motions over the roadway in parallel wind cases which may be due to the mechanical turbulence generated by the traffic flow. The dispersion parameter values computed from the concentration measurements agree very closely to those prescribed for neutral conditions in the GM model and unstable conditions in the HIWAY model.It is suggested that the stability adjacent to the roadway may be determined either through bulk Richardson number, or wind fluctuation data obtained at the site. Further, a better formulation of the dispersion parameters may be σ_z ~ σ_σx, and σ_y ~ σ_θx, rather than the power law relationship (σ_z ~ α₁x^b₁ andσ_y ~ α₂x^b₂) commonly used in the existing highway dispersion models. In this regard, wind fluctuation statistics sampled for a duration of one hour are appropriate for describing the dispersion mechanism near roadways.     

Develop dynamic model for predicting traffic CO emissions in urban areas

The greater the use of energy in the transportation sectors, the higher the emission of carbon monoxide (CO), and hence inevitable harm to environment and human health. In this concern, measuring and predicting of CO emission from transportation sector—especially large cities—is important as it constitute 90 % of all CO emission. Many urban cities in developing world have not properly experienced such measurements or predictions. In this paper, for the first time, field measurements of traffic characteristics data and corresponding CO concentration have been performed for developing a model for predicting CO emissions from transportation sector for New Borg El Arab (NBC), Egypt. The performance of Swiss-German Handbook Emission Factors for Road Transport (HBEFA v3.1) model has been assessed for predicting the CO concentration at roadside in the study area. Results indicated that HBEFA v3.1 underestimate emission figures. The developed CO dynamic emission model involves the traffic flow characteristics with roadside CO concentrations. Acceptable representation of measured CO concentration has been shown by the developed dynamic CO emission model which introduces R ²?=?0.77, mean biases and frictional biases of ?0.27 mg m^?3 and 0.09, respectively. A comparison between predicted CO concentrations using HBEFA v3.1 and the promoted dynamic model indicate that HBEFA v3.1 estimates CO emission concentrations in the study area with a mean error and frictional biases 159.26 and 233.33 %, respectively, higher than those of the developed model.     

The effects of roadside structures on the transport and dispersion of ultrafine particles from highways

Understanding local-scale transport and dispersion of pollutants emitted from traffic sources is important for urban planning and air quality assessments. Predicting pollutant concentration patterns in complex environments depends on accurate representations of local features (e.g., noise barriers, trees, buildings) affecting near-field air flows. This study examined the effects of roadside barriers on the flow patterns and dispersion of pollutants from a high-traffic highway in Raleigh, North Carolina, USA. The effects of the structures were analyzed using the Quick Urban & Industrial Complex (QUIC) model, an empirically based diagnostic tool which simulates fine-scale wind field and dispersion patterns around obstacles. Model simulations were compared with the spatial distributions of ultrafine particles (UFP) from vehicular emissions measured using a passenger van equipped with a Differential Mobility Analyzer/Condensation Particle Counter. The field site allowed for an evaluation of pollutant concentrations in open terrain, with a noise barrier present near the road, and with a noise barrier and vegetation present near the road.Results indicated that air pollutant concentrations near the road were generally higher in open terrain situations with no barriers present; however, concentrations for this case decreased faster with distance than when roadside barriers were present. The presence of a noise barrier and vegetation resulted in the lowest downwind pollutant concentrations, indicating that the plume under this condition was relatively uniform and vertically well-mixed. Comparison of the QUIC model with the mobile UFP measurements indicated that QUIC reasonably represented pollutant transport and dispersion for each of the study configurations.     

The impact of the congestion charging scheme on ambient air pollution concentrations in London

On 17th February 2003, a congestion charging scheme (CCS), operating Monday–Friday, 07:00–18:00, was introduced in central London along with a programme of traffic management measures. We investigated the potential impact of the introduction of the CCS on measured pollutant concentrations (oxides of nitrogen (NO_X, NO and NO₂), particles with a median diameter less than 10 microns (PM₁₀), carbon monoxide (CO) and ozone (O₃)) measured at roadside and background monitoring sites across Greater London. Temporal changes in pollution concentrations within the congestion charging zone were compared to changes, over the same time period, at monitors unlikely to be affected by the CCS (the control zone) and in the boundary zone between the two. Similar analyses were done for CCS hours during weekends (when the CCS was not operating).Based on the single roadside monitor with the CCS Zone, it was not possible to identify any relative changes in pollution concentrations associated with the introduction of the scheme. However, using background monitors, there was good evidence for a decrease in NO and increases in NO₂ and O₃ relative to the control zone. There was little change in background concentrations of NO_X. There was also evidence of relative reductions in PM₁₀ and CO. Similar changes were observed during the same hours in weekends when the scheme was not operating.The causal attribution of these changes to the CCS per se is not appropriate since the scheme was introduced concurrently with other traffic and emissions interventions which might have had a more concentrated effect in central London. This study provides important pointers for study design and data requirements for the evaluation of similar schemes in terms of air quality. It also shows that results may be unexpected and that the overall effect on toxicity may not be entirely favourable.     

A measurement campaign in a street canyon in Helsinki and comparison of results with predictions of the OSPM model

In 1997, a measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki. Hourly mean concentrations of CO, NO_x, NO₂ and O₃ were measured at street and roof levels, the latter in order to determine the urban background concentrations. The relevant hourly meteorological parameters were measured at roof level; these included wind speed and direction, temperature and solar radiation. Hourly street level measurements and on-site electronic traffic counts were conducted throughout the whole of 1997; roof level measurements were conducted for approximately two months, from 3 March to 30 April in 1997. CO and NO_x emissions from traffic were computed using measured hourly traffic volumes and evaluated emission factors. The Operational Street Pollution Model (OSPM) was used to calculate the street concentrations and the results were compared with the measurements. The overall agreement between measured and predicted concentrations was good for CO and NO_x (fractional bias were −4.2 and +4.5%, respectively), but the model overpredicted the measured NO₂ concentrations (fractional bias was +22%). The agreement between the measured and predicted values was also analysed in terms of its dependence on wind speed and direction; the latter analysis was performed separately for two categories of wind velocity. The model qualitatively reproduces the observed behaviour very well. The database, which contains all measured and predicted data, is available for further testing of other street canyon dispersion models. The dataset contains a larger proportion of low wind speed cases, compared with other available street canyon measurement datasets.     

Metal translocation patterns in Solanum melongena grown in close proximity to traffic

The purpose of this study is to examine tissue patterns of metal (Cr, Ni, Cu, Cd, and Pb) concentrations in Solanum melongena cultivated in close proximity to traffic to help elucidate associated elemental deposition and soil-to-root and root-to-shoot transfers. Plants were cultivated in a commercial soil mix at three sites in Toronto, Canada. Metal concentrations were determined on microwave-digested bulk and rhizosphere soil and tissue samples per ICP-MS, along with two standard reference materials (NIST #1570a and #2709a). Unwashed and washed S. melongena samples were also analyzed, along with Origanum vulgare plants from the same sites, to assess the effectiveness of washing in reducing metal concentrations. The tissue distribution of Cr, Ni, Cu, and Pb demonstrated variability as a function of traffic proximity. Copper was found to easily translocate to roots in soils susceptible to waterlogging, while Cd had the highest soil-to-root and root-to-shoot translocation. The translocation of Cd was highest at the roadside site, due to a greater relative enrichment of this metal in the rhizosphere of S. melongena plants. Washing O. vulgare leaves was more effective in removing metal-associated particles compared to S. melongena samples. Cadmium uptake is of greatest concern given its toxicity and translocation potential.     

Development of a distance-to-roadway proximity metric to compare near-road pollutant levels to a central site monitor

The primary objective of the Detroit Exposure and Aerosol Research Study (DEARS) was to compare air pollutant concentrations measured at various neighborhoods, or exposure monitoring areas (EMAs), throughout a major metropolitan area to levels measured at a central site or community monitor. One of the EMAs was located near a busy freeway (annual average daily traffic (AADT) of ～130,000) so that impacts of mobile sources could be examined. Air pollution concentrations from the roadway-proximate sites were compared to the central site monitor. The volatile organic compounds (VOCs) selected (benzene, toluene, ethylbenzene, m,p- and o-xylene, 1,3 butadiene, 1,3,5-trimethylbenzene and 4-ethyltoluene) are typically associated with mobile sources. Gradients were also evident that demonstrated the amplification of pollutant levels near the roadway compared to the community monitor. A novel distance-to-roadway proximity metric was developed to plot the measurements and model these gradients. Effective distance represents the actual distance an air parcel travels from the middle of a roadway to a site and varies as a function of wind direction, whereas perpendicular distance is a fixed distance oriented normal to the roadway. Perpendicular distance is often used as a proxy for exposures to traffic emissions in epidemiological studies.Elevated concentrations of all the compounds were found for both a summer and winter season. Effective distance was found to be a statistically significant (p < 0.05) univariate predictor for concentrations of toluene, ethylbenzene, m,p-xylene and o-xylene for summer 2005. For each of these pollutants, effective distance yielded lower p-values than the corresponding perpendicular distance models, and model fit improved. Results demonstrate that this near-road EMA had elevated levels of traffic-related VOCs compared to the community monitor, and that effective distance was a more accurate predictor of the degree to which they were elevated as a function of distance. Effective distance produced a range of distance-to-roadway values for a single site based on wind direction, thus increasing the number and range of values that could be used to plot and predict relative differences in pollutant concentrations between two sites.     

Characterizing and predicting coarse and fine particulates in classrooms located close to an urban roadway

The PM₁₀, PM_2.5, and PM₁ (particulate matter with aerodynamic diameters <10, <2.5, and <1 μm, respectively) concentrations were monitored over a 90-day period in a naturally ventilated school building located at roadside in Chennai City. The 24-hr average PM₁₀, PM_2.5, and PM₁ concentrations at indoor and outdoor environments were found to be 136 ± 60, 36 ± 15, and 20 ± 12 and 76 ± 42, 33 ± 16, and 23 ± 14 μg/m³, respectively. The size distribution of PM in the classroom indicated that coarse mode was dominant during working hours (08:00 a.m. to 04:00 p.m.), whereas fine mode was dominant during nonworking hours (04:00 p.m. to 08:00 a.m.). The increase in coarser particles coincided with occupant activities in the classrooms and finer particles were correlated with outdoor traffic. Analysis of indoor PM₁₀, PM_2.5, and PM₁ concentrations monitored at another school, which is located at urban reserved forest area (background site) indicated 3–4 times lower PM₁₀ concentration than the school located at roadside. Also, the indoor PM₁ and PM_2.5 concentrations were 1.3–1.5 times lower at background site. Further, a mass balance indoor air quality (IAQ) model was modified to predict the indoor PM concentration in the classroom. Results indicated good agreement between the predicted and measured indoor PM_2.5 (R² = 0.72–0.81) and PM₁ (R² = 0.81–0.87) concentrations. But, the measured and predicted PM₁₀ concentrations showed poor correlation (R² = 0.17–0.23), which may be because the IAQ model could not take into account the sudden increase in PM₁₀ concentration (resuspension of large size particles) due to human activities.

Implications:The present study discusses characteristics of the indoor coarse and fine PM concentrations of a naturally ventilated school building located close to an urban roadway and at a background site in Chennai City, India. The study results will be useful to engineers and policymakers to prepare strategies for improving the IAQ inside classrooms. Further, this study may help in the development of IAQ standards and guidelines in India.     

Roadside and in-vehicle concentrations of monoaromatic hydrocarbons

Airborne concentrations of benzene, toluene and the xylenes have been measured inside passenger cars whilst driven along major roads in the city of Birmingham, UK, as well as immediately outside the car, and at the roadside. A comparison of concentrations measured in the car with those determined from immediately outside showed little difference, with a mean ratio for benzene of 1.17±0.34 and for toluene 1.11±0.16 (n=53). The ratio of in-car to roadside concentration was rather higher at 1.55±0.68 for benzene and 1.54±0.72 for toluene (n=53). The roadside concentrations were typically several-fold higher than those measured at a background suburban monitoring station within Birmingham, although much variation was seen between congested and uncongested roads, with concentrations adjacent to uncongested roads similar to those measured at the background monitoring station. Measurements of benzene and toluene in a car driven on a rural road outside the city showed very comparable in-car and out-of-car concentrations strengthening the conclusion that pollution inside the car is derived from pollutants outside entering with ventilation air. The exceptions were an older car where in-car concentrations appreciably exceeded those outside (in-to out-vehicle ratio=2.3 for benzene and 2.2 for toluene where n=5) indicating probable self-contamination, and a very new car which built up increased VOC concentrations when stationary without ventilation (in-to out-vehicle ratio=2.4 for benzene and 3.3 for toluene where n=5). A further set of measurements inside London taxi cabs showed concentrations to be influenced by the area within which the taxi was driven, the traffic density and the presence of passengers smoking cigarettes.     

Spatio-temporal covariation of urban particle number concentration and ambient noise

Mobile measurements of ambient noise and particle number concentrations were carried out within an urban residential area in Essen, Germany, during summer 2008. A busy major road with a traffic intensity of about 44,000 vehicles per day was situated within the study area. The spatio-temporal distribution of noise and particles was closely coupled to road traffic on the major road. Total particle number concentrations in proximity to the main road were on average between 25,000 cm^?3 and 35,000 cm^?3 while sound levels reached 70–78 dB(A). These estimates were more than double-fold (factor 2.4) in comparison to the urban residential background. At a 50 m distance off the road particle number concentrations were decaying to about 50% of the initial value. The measurements were characterised by close spatial correlation between total particle number concentration and ambient noise with correlation coefficients of up to r = 0.74. However, during one measurement day coupling between both quantities was weak due to higher turbulent mixing within the canopy layer and a change in ambient wind directions. Enhanced dilution of particle emission from road traffic by turbulent mixing and ‘decoupling’ from the influence of road traffic are believed to be responsible.     

Evaluation of the CAR-FMI model against measurements near a major road

A field measurement campaign was conducted near a major road in southern Finland from September 15 to October 30, 1995. The concentrations of NO, NO₂ and O₃ were measured simultaneously at three locations, at three heights (3.5, 6 and 10 m) on both sides of the road. Traffic densities and relevant meteorological parameters were also measured on-site. We have compared measured concentration data with the predictions of the road network dispersion model CAR-FMI, used in combination with a meteorological pre-processing model MPP-FMI. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted datasets was good, as measured using various statistical parameters. For all data (N=587), the index of agreement (IA) was 0.83, 0.82 and 0.89 for the measurements of NO_x, NO₂ and O₃, respectively. The IA is a statistical measure of the correlation of the predicted and measured time series of concentrations. However, the modelling system overpredicts NO_x concentrations with a fractional bias FB=+13%, and O₃ concentrations with FB=+8%, while for NO₂ concentrations FB=−2%. We also analyzed the difference between model predictions and measured data in terms of meteorological parameters. Model performance clearly deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. The range of variability concerning atmospheric stability, ambient temperature and the amount of solar radiation was modest during the measurement campaign. As expected, no clear dependencies of model performance were therefore detected in terms of these parameters. The experimental dataset is available for the evaluation of other roadside dispersion models.     

Impact of roadside noise barriers on particle size distributions and pollutants concentrations near freeways

Increasing epidemiological evidence has established an association between a host of adverse health effects and exposure to ambient particulate matter (PM) and co-pollutants, especially those emitted from motor vehicles. Although PM and their co-pollutants dispersion profiles near the open freeway have been extensively characterized by means of both experimental measurements and numerical simulations in recent years, such investigations near freeways with roadside barriers have not been well documented in the literature. A few previous studies suggested that the presence of roadside structures, such as noise barriers and vegetation, may impact the decay of pollutant concentrations downwind of the freeway by limiting the initial dispersion of traffic emissions and increasing their vertical mixing due to the upward deflection of airflow. Since the noise barriers are now common roadside features of the freeways, particularly those running through populated urban areas, it is pertinent to investigate the impact of their presence on the particles and co-pollutants concentrations in areas adjacent to busy roadways. This study investigated two highly trafficked freeways (I-710 and I-5) in Southern California, with two sampling sites for each freeway, one with and the other without the roadside noise barriers. Particle size distributions and co-pollutants concentrations were measured in the immediate proximity of freeways and at different distances downwind of the freeways. The results showed the formation of a “concentration deficit” zone in the immediate vicinity of the freeway with the presence of roadside noise barrier, followed by a surge of pollutant concentrations further downwind at 80–100 m away from freeway. The particle and co-pollutants concentrations reach background levels at farther distances of 250–400 m compared to 150–200 m at the sites without roadside noise barriers.     

Estimation of particle resuspension source strength on a major London Road

Non-exhaust particles from road traffic arise from both abrasion sources and the resuspension of particles from the road surface. This paper reports a new combination of existing methods for indirect estimation of resuspension emission factors for Marylebone Road, London, a busy multi-lane highway in a street canyon. The method involves firstly estimating the total source strength of coarse particles (PM_2.5–10) arising from the road by calculating the roadside incremental concentration of coarse particles above the urban background. This is converted to a source strength by its ratio to NO_x whose source strength is estimated from the knowledge of the traffic mix and mean speed. This coarse particle source strength is assumed to represent the sum of resuspension emissions and the coarse particle component of abrasion emissions. Using information on the traffic mix and speed, the abrasion emissions have been calculated from the EMEP/CORINAIR emissions factor database, the result subtracted from the total coarse particle emissions in order to yield resuspension emissions, and combined with traffic count data to derive fleet-average emission factors. Using the fact that the traffic mix differs substantially between weekdays and weekends, separate average emission factors for light- and heavy-duty vehicles have been estimated. In addition to traffic mix, the influence of wind speed and the time elapsed since the last rainfall upon resuspension have been estimated. Wind speed was found to have by far the larger influence, although this was still secondary to the number of heavy-duty vehicles. Uncertainties arising from the choice of urban background site and poor data quality are discussed.     

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.     

Roadside suspended particulates at heavily trafficked urban sites of Hong Kong – Seasonal variation and dependence on meteorological conditions

In this study, the seasonal variation of different types of particulates was investigated in a fixed roadside station in heavily trafficked urban area of Hong Kong. Aerosol samples for total suspended particles (TSP), PM₁₀ and PM_2.5 were collected from June 1998 to May 1999 at a roadside site. Meteorological conditions such as relative humidity (RH), rainfall and prevailing wind direction were found to affect the mass concentration of TSP, PM₁₀ and coarse particulates at roadside level. Large size particles had an apparent seasonal variation, with higher concentration level in winter and lower in summer. The dry continental winter monsoon and the wet oceanic summer monsoon are the dominating factors. On the other hand, annual variation of PM_2.5 is relatively insignificant, suggesting that they are mainly from local traffic emission. PM₁₀ accounted for 62% of the TSP, while PM_2.5 accounted for 46%. The annual PM_2.5/PM₁₀ is high with PM_2.5 responsible for 74% of PM₁₀. In our heavily trafficked roadside fixed site, TSP exceeded the annual average of the Hong Kong Air Quality Objective by a factor of 1.53 while PM₁₀ exceeded by 1.39. The annual average concentration of PM_2.5 exceeded the National Ambient Air Quality Standard (NAAQS) annual average of 15 μg m⁻³ by a factor of 3.8 and is a cause of concern. A total of the 24 h average PM_2.5 exceeded NAAQS by 33%. According to our data reported, fine particulate pollution is serious in Hong Kong.     

A study of surface ozone and the relation to complex wind flow in Hong Kong

Ozone measurements made from 5 sites in Hong Kong have been analyzed, including those from one upwind, one downwind, and three urban locales. The data are analyzed in terms of the seasonal and diurnal trends. A subset of data in autumn is further analyzed to study the relationship between the ozone spatial pattern and wind flow as well as other meteorological parameters. The results show that averaged ozone levels at most sites exhibit maxima in autumn, which appears to be a unique feature for eastern Asia. On average the daily maximum 1-h concentrations are found to be higher in the western (normally downwind) site than those on the eastern side and in urban areas. Examination of surface wind patterns and other meteorological parameters suggest that elevated ozone concentrations on the western side occur during the days with intense solar radiation, light winds, and in the presence of a unique wind circulation. The wind reversal in the western parts under the “convergence” flow is believed to be an important cause of the high-ozone events observed there. Such wind flow may re-circulate/transport nearby urban plumes (in this case the Hong Kong–Shenzhen urban complex). Examination of chemical data from the western site has shown that averaged afternoon SO₂ to NO_x ratios on days with wind reversal are larger than those of typical urban Hong Kong and that a significant SO₂ enhancement was clearly indicated on several occasions. The SO₂ enhancement may be interpreted as being the evidence to suggest the contribution of regional sources and/or Hong Kong’s power plants (both containing high SO₂). A case study has shown that when moderately strong northwesterly wind prevails, elevated ozone and SO₂ can be transported to western Hong Kong from the inner Pearl Delta region. This study has also indicated that under the impact of ENE winds the eastern side of Hong Kong is not frequently affected by the re-circulating ozone plumes present in the western side.     

Characterisation of fresh particulate vehicular exhausts near a Paris high flow road

Simultaneous continuous measurements of PM_2.5, PM₁₀, black carbon mass (BCae), Black smoke (BS) and particle number density (N) were conducted in the close vicinity of a high traffic road around Paris during a three-month period beginning in August 1997. In parallel some aerosol collection was performed on filters in order to assess the black carbon (BC), organic carbon (OC) and water soluble organic fractions (WSOC) of the freshly emitted traffic aerosols. The high hourly concentrations of PM_2.5 (39±20 μg m⁻³), BCae (14±7 μg m⁻³), and N (220,000±115,000 cm⁻³), were found to be well correlated with each other. On average PM_2.5 represented 66±13% of PM₁₀ and appears to be composed primarily of BC (43±20%). On the contrary no correlation was found between PM_2.5 and the coarse (PM₁₀–PM_2.5) mass fractions which was attributed to resuspension processes by vehicles. Black carbon mass concentrations obtained from both filter analyses (BC) and Aethalometre data (BCae) show a good agreement suggesting that the Aethalometre calibration based on a black carbon specific attenuation coefficient (σ) of 19 m² g⁻¹ is well adapted to nearby roadside measurements. Daily BC (used as a surrogate for fine particles) concentrations and wind speed were found to be anti-correlated. Average daily variations of BC could be related to traffic intensity and regime as well as to the boundary layer height. As expected for freshly emitted traffic aerosols, filter analyses indicated a high BC/TC ratio (29±5%) and a low mean WSOC/OC ratio (12.5±5%) for the bulk aerosol. For these two ratios no day/night differences were observed, the sampling station being probably too close to traffic to evidence photochemical modification of the aerosol phase. Finally, a linear relationship was found between BC and BS hourly concentrations (BC=0.10×BS+1.18; r²=0.93) which offers interesting perspectives to retrieve BC concentrations from existing BS archives.     

Operational air pollution modelling in the UK—Street canyon applications and challenges

Local air quality management requires the use of screening and advanced modelling tools that are able to predict roadside pollution levels under a variety of meteorological and traffic conditions. So far, more than 200 air pollution hotspots have been identified by local authorities in the UK, many of them associated with NO₂ and/or PM₁₀ exceedences in heavily trafficked urban streets that may be classified as street canyons or canyon intersections. This is due to the increased traffic-related emissions and reduced natural ventilation in such streets. Specialised dispersion models and empirical adjustment factors have been commonly used to account for the entrapment of pollutants in street canyons. However, most of the available operational tools have been validated using experimental datasets from relatively deep canyons (H/W⩾1) from continental Europe. The particular characteristics of low-rise street canyons (H/W<1), which are a typical feature of urban/sub-urban areas in the UK, have been rarely taken into account.The main objective of this study is to review current practice and evaluate three widely used regulatory dispersion models, WinOSPM, ADMS-Urban 2.0 and AEOLIUS Full. The model evaluation relied on two comprehensive datasets, which included CO, PM₁₀ and NO_x measurements, traffic information and relevant meteorological data from two busy street canyons in Birmingham and London for a 1-year period. The performance of the selected models was tested for different times of the day/days of the week and varying wind conditions. Furthermore, the ability of the models to reproduce roadside NO₂/NO_x concentration ratios using simplified chemistry schemes was evaluated for one of the sites. Finally, advantages and limitations of the current regulatory street canyon modelling practice in the UK, as well as needs for future research, have been identified and discussed.     

Differences in airborne particle and gaseous concentrations in urban air between weekdays and weekends

Airborne particle number concentrations and size distributions as well as CO and NO_x concentrations monitored at a site within the central business district of Brisbane, Australia were correlated with the traffic flow rate on a nearby freeway with the aim of investigating differences between weekday and weekend pollutant characteristics. Observations over a 5-year monitoring period showed that the mean number particle concentration on weekdays was (8.8±0.1)×10³ cm⁻³ and on weekends (5.9±0.2)×10³ cm⁻³—a difference of 47%. The corresponding mean particle number median diameters during weekdays and weekends were 44.2±0.3 and 50.2±0.2 nm, respectively. The differences in mean particle number concentration and size between weekdays and weekends were found to be statistically significant at confidence levels of over 99%. During a 1-year period of observation, the mean traffic flow rate on the freeway was 14.2×10⁴ and 9.6×10⁴ vehicles per weekday and weekend day, respectively—a difference of 48%. The mean diurnal variations of the particle number and the gaseous concentrations closely followed the traffic flow rate on both weekdays and weekends (correlation coefficient of 0.86 for particles). The overall conclusion, as to the effect of traffic on concentration levels of pollutant concentration in the vicinity of a major road (about 100 m) carrying traffic of the order of 10⁵ vehicles per day, is that about a 50% increase in traffic flow rate results in similar increases of CO and NO_x concentrations and a higher increase of about 70% in particle number concentration.     

Near-roadway monitoring of vehicle emissions as a function of mode of operation for light-duty vehicles

Determination of the effect of vehicle emissions on air quality near roadways is important because vehicles are a major source of air pollution. A near-roadway monitoring program was undertaken in Chicago between August 4 and October 30, 2014, to measure ultrafine particles, carbon dioxide, carbon monoxide, traffic volume and speed, and wind direction and speed. The objective of this study was to develop a method to relate short-term changes in traffic mode of operation to air quality near roadways using data averaged over 5-min intervals to provide a better understanding of the processes controlling air pollution concentrations near roadways. Three different types of data analysis are provided to demonstrate the type of results that can be obtained from a near-roadway sampling program based on 5-min measurements: (1) development of vehicle emission factors (EFs) for ultrafine particles as a function of vehicle mode of operation, (2) comparison of measured and modeled CO₂ concentrations, and (3) application of dispersion models to determine concentrations near roadways. EFs for ultrafine particles are developed that are a function of traffic volume and mode of operation (free flow and congestion) for light-duty vehicles (LDVs) under real-world conditions. Two air quality models—CALINE4 (California Line Source Dispersion Model, version 4) and AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model)—are used to predict the ultrafine particulate concentrations near roadways for comparison with measured concentrations. When using CALINE4 to predict air quality levels in the mixing cell, changes in surface roughness and stability class have no effect on the predicted concentrations. However, when using AERMOD to predict air quality in the mixing cell, changes in surface roughness have a significant impact on the predicted concentrations.

Implications: The paper provides emission factors (EFs) that are a function of traffic volume and mode of operation (free flow and congestion) for LDVs under real-world conditions. The good agreement between monitoring and modeling results indicates that high-resolution, simultaneous measurements of air quality and meteorological and traffic conditions can be used to determine real-world, fleet-wide vehicle EFs as a function of vehicle mode of operation under actual driving conditions.