Air pollution dispersion within urban street canyons

A semi-empirical mathematical model, Urban Street Model (USM), is proposed to efficiently estimate the dispersion of vehicular air pollution in cities. This model describes urban building arrangements by combining building density, building heights and the permeability of building arrangements relative to wind flow. To estimate the level of air pollution in the city of Krasnoyarsk (in Eastern Siberia), the spatial distribution of pollutant concentrations off roadways is calculated using Markov's processes in USM. The USM-predicted numerical results were compared with field measurements and with results obtained from other frequently used models, CALINE-4 and OSPM. USM consistently yielded the best results. OSPM usually overestimated pollutant concentration values. CALINE-4 consistently underestimated these values. For OSPM, the maximum differences were 160% and for CALINE-4 about 400%. Permeability and building density are necessary parameters for accurately modeling urban air pollution and influencing regulatory requirements for building planning.     

A Preliminary Study of Modeling the Air Pollution Effects fromTraffic Engineering Alternatives

Three separate mathematical models were combined to calculate the changes in carbon monoxide (CO) concentrations that might result from traffic engineering changes. The three models used were: (1) The Dynamic Highway Transportation model (DHTM) which relates traffic flow patterns to physical parameters and traffic signal characteristics of a network; (2) an emission model that predicts CO emissions from traffic flow parameters such as number of stops, idling time, etc; and (3) the APRAC-1A urban diffusion model which calculates CO concentrations from source distributions and meteorological factors. The composite model was applied to traffic in downtown Chicago for a specific set of meteorological conditions. Results are compared for two traffic signal control schemes. In those blocks where concentrations were highest, the model indicates a 20% reduction is possible through improved traffic signal controls. The model should be useful for testing other traffic control measures.     

Prediction of PM10 concentrations at urban traffic intersections using semi-empirical box modelling with instantaneous velocity and acceleration

At urban traffic intersections, vehicles frequently stop with idling engines during the red-light period and speed up rapidly during the green-light period. The changes of driving patterns (i.e., idle, acceleration, deceleration and cruising patterns) generally produce uncertain emission. Additionally, the movement of pedestrians and the influence of wind further result in the random dispersion of pollutants. It is, therefore, too complex to simulate the effects of such dynamics on the resulting emission using conventional deterministic causal models.For this reason, a modified semi-empirical box model for predicting the PM₁₀ concentrations on roadsides is proposed in this paper. The model constitutes three parts, i.e., traffic, emission and dispersion components. The traffic component is developed using a generalized force traffic model to obtain the instantaneous velocity and acceleration when vehicles move through intersections. Hence the distribution of vehicle emission in street canyon during the green-light period is calculated. Then the dispersion component is investigated using a semi-empirical box model combining average wind speed, box height and background concentrations. With these considerations, the proposed model is applied and evaluated using measured data at a busy traffic intersection in Mong Kok, Hong Kong. In order to test the performance of the model, two situations, i.e., the data sets within a sunny day and between two sunny days, were selected to examine the model performance. The predicted values are generally well coincident with the observed data during different time slots except several values are overestimated or underestimated. Moreover, two types of vehicles, i.e., buses and petrol cars, are separately taken into account in the study. Buses are verified to contribute most to the emission in street canyons, which may be useful in evaluating the impact of vehicle emissions on the ambient air quality when there is a significant change in a specific vehicular population.     

Principal Plume Dispersion Models: TVA Power Plants

The body of information presented in this paper is directed to those individuals who may be concerned with principal plume dispersion models at coal-burning power plants. About 20 years of comprehensive field surveillance and documentation of dispersion of power plant emissions for a varied range of unit sizes, stack heights, and meteorological conditions have determined the Tennessee Valley Authority’s interpretation of principal plume dispersion models. TVA’s experience indicates that as unit sizes are increased and taller stacks are constructed, the plume dispersion model associated with maximum surface concentrations changes. Maximum surface concentrations for principal plume dispersion models were approximately equal for the early small plants. However, the coning model was considered the critical plume dispersion model because the frequency of recurrence of surface concentrations from this model was appreciably greater than other models.

There were progressive changes because of an increase in unit sizes and stack heights; the magnitude of maximum surface concentrations from the coning model decreased, and the magnitude (relative to the coning model) of concentrations from the inversion breakup model increased. However, with plumes from newer and larger units with higher stacks, the trapping dispersion model became prominent. Finally, by the time unit size had increased to 900 mw and stack height to about 245 meters, as at Bull Run Power Plant, the magnitude of surface concentrations associated with trapping had increased to such a degree that it became the critical dispersion model identified with power plants of this size.     

Modeling traffic-related air pollution in street canyons of Beijing

It is important to develop a general model to accurately simulate the air pollution in urban street areas. In this paper, the Operational Street Pollution Model (OSPM) initially developed in Denmark is tested with measured data from a relatively wide and open street in Beijing. Major factors influencing the dispersion, such as emission factors, stationary source emissions, and solar radiation, are analyzed. Results show that the model can reflect the basic dispersion pattern in the street but gives systematically higher concentrations. After modifications to estimate street-level wind speed in the model, performance is obviously improved.     

Application of a Three-Layer Photochemical Box Model in an Athens Street Canyon

ABSTRACT

The aim of this paper is to show that a photochemical box model could describe the air pollution diurnal profiles within a typical street canyon in the city of Athens. As sophisticated three-dimensional dispersion models are computationally expensive and they cannot serve to simulate pollution levels in the scale of an urban street canyon, a suitably modified three-layer photochemical box model was applied. A street canyon of Athens with heavy traffic was chosen to apply the aforementioned model. The model was used to calculate pollutant concentrations during two days with meteorological conditions favoring pollutant accumulation. Road traffic emissions were calculated based on existing traffic load measurements. Meteorological data, as well as various pollutant concentrations, in order to compare with the model results, were provided by available measurements. The calculated concentrations were found to be in good agreement with measured concentration levels and show that, when traffic load and traffic composition data are available, this model can be used to predict pollution episodes. It is noteworthy that high concentrations persisted, even after additional traffic restriction measures were taken on the second day because of the high pollution levels.     

Modeling Traffic-Related Air Pollution in Street Canyons of Beijing

ABSTRACT

It is important to develop a general model to accurately simulate the air pollution in urban street areas. In this paper, the Operational Street Pollution Model (OSPM) initially developed in Denmark is tested with measured data from a relatively wide and open street in Beijing. Major factors influencing the dispersion, such as emission factors, stationary source emissions, and solar radiation, are analyzed. Results show that the model can reflect the basic dispersion pattern in the street but gives systematically higher concentrations. After modifications to estimate street-level wind speed in the model, performance is obviously improved.     

The Use of Artificial Activable Trace Elements to Monitor Pollutant Source Strengths and Dispersal Patterns

A tracer technique using certain of the rare earth elements which are easily activated by neutrons has been developed for the analysis of air pollution problems. Studies employing these tracers were made to determine whether the available meteorological dispersion models can be used effectively to describe pollution emissions from selected industries in the vicinity of Albany, Oregon. The Gaussian plume model was found to be satisfactory for the moderately intense turbulence fields which characterize Stability Types B, C, and D, including cases in which the pollution was trapped by an inversion layer aloft. For sources near ground level, however, it was necessary to make allowance for urban influences on plume dispersion. A box model best described the observed dispersal pattern when the upward penetration of the very intense turbulence of Stability Type A was limited by an inversion layer aloft. These meteorological models were applied using a “blind” experimental procedure to predict the emission rates of the effluent from multiple sources of air pollution in the Albany area. It was found that these techniques can be used to predict the rate of emission within a factor of two for multiple sources consisting of three stacks.     

Adherence of Sulfur Dioxide Concentrations in the Vicinity of a Steam Plant to Plume Dispersion Models

Air monitoring data for a calendar year at one of the TVA power plants has been used to evaluate the appropriateness of the Sutton, the Bosanquet and Pearson, and the USPHS-TVA atmospheric dispersion models to predict ground level concentrations of sulfur dioxide from emission and meterological data. Aerometric data included one half hourly average sulfur dioxide concentrations, recorded by four Thomas autometers, and the necessary meterological parameters for the solving of atmospheric dispersion models. Based on these meterological parameters and observed plume rise data, over 4000 one half hourly average maximum and minimum expected ground line sulfur dioxide concentrations were predicted for each of the above dispersion models by the use of computer techniques. The plant is a line source; however, an empirical correction was applied to emission data to reduce them to emissions for an equivalent point source. The predicted sulfur dioxide levels for each of the dispersion models were compared to the measured levels throughout the year. Three different sets of diffusion coefficients were applied to the Sutton model and successful predictions, according to a criterion utilizing an acceptable range of concentration, varied from 66 to 93%. The Bosanquet and Pearson model produced successful predictions 90% of the time, while the USPHS-TVA model was successful 94% of the time.Unsuccessful predictions were primarily overestimates.     

Near-Field Dispersion Modeling for Regulatory Applications

Abstract

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex–Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model–Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

An evaluation of the estimation of road traffic emission factors from tracer studies

Road traffic emission factors (EFs) are one of the main sources of uncertainties in emission inventories; it is necessary to develop methods to reduce these uncertainties to manage air quality more efficiently. Recently an alternative method has been proposed to estimate the EFs. In that work the emission factors were estimated from a long term tracer study developed in Ho Chi Minh City (HCMC) Vietnam. A passive tracer was continuously emitted from a finite line source placed in one side of an urban street canyon. Simultaneously, the resulting tracer concentrations were monitored at the other side of the street. The results of this experiment were used to calculate the dispersion factors and afterwards, these dispersion factors were used to estimate the EFs. In this paper we use the Computational Fluids Dynamics (CFD) model WinMISKAM to critically evaluate the proposed methodology.In a first step, we use the results of the tracer study to validate the CFD model. Results show that the model is able to simulate quite well the tracer dispersion in most of the cases. The model is then used to evaluate the effect of varying the source configuration and to correct the EFs. A comparison with available studies shows that the corrected EFs are within the range of the EFs reported in other studies. Finally, the CFD model is used to find a source configuration that better represents the vehicle emissions and that may be used in future studies to estimate the EFs more accurately. Results show that a 200 m line placed in the center of the street would represent very well the vehicle emissions. This work shows that it is possible to accurately estimate the EFs from tracer studies.     

Wind-tunnel study of concentration fields in street canyons

The paper presents results from a case study of gaseous pollutant dispersion in street canyons. Tracer-gas experiments were performed in a neutrally stratified wind tunnel. Vehicle emissions were simulated as line sources. Concentration profiles along building walls were measured. A two-dimensional street canyon was considered as the reference case. The influence of systematic parameter variations on the concentration field is studied and discussed. Building dimensions, upwind building configuration, wind direction and roof geometry were found to be important parameters. Data sets from the study may be used for evaluation of numerical models and for expert estimates of air quality in the urban environment     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.     

Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

湍流扩散方程数学解析的探讨

本文讨论了水流场中平流、分子扩散、湍流扩散、离散作用所引起的扩散物质质量通量的数学解析以及几种水质数学模型的应用条件。     

Mesoscale modeling of wintertime particulate matter episodes in eastern Washington, USA

The Spokane, Washington area is classified as a non-attainment area for the 24-h PM₁₀ standard due to a history of high particulate matter concentrations. A Eulerian regional air quality model (CALMET/CALGRID) has been used to characterize the emission, transport and dispersion of PM₁₀ and PM_2.5 in Spokane. Observations from a residential site (Rockwood, RW) and an industrial site (Crown Zellerbach, CZ), spanning July 1994–August 1996 were used to evaluate the current emission inventory. Two major tasks were devised to conduct the objectives of this investigation. First, a simple and efficient urban dispersion model (WYNDValley) was used to simulate important episodes characterized by the highest PM₁₀ and PM_2.5 concentrations. The selected episodes included four days with wet conditions for which no roads would have been emitting and seven days with dry conditions for which roads would emit. In the second step, a single road-emitting event was selected from the previous predicted results for further analysis using the Eulerian regional air quality model to examine the emission inventory. The urban and regional models predicted the observed concentration distributions reasonably well for the source emissions inventoried in Spokane. The mass concentrations of PM₁₀ were well predicted for the roads emitting case examined by both models indicating that the emission inventory based primarily upon area sources including roads is reasonably well characterized, at least at the RW site. The area sources around CZ are less well characterized, so that the PM₁₀ concentrations are underpredicted at CZ. The models appear unable to reach an equilibrium mass balance status at the beginning of the simulation, and the urban model seems unable to properly resolve the nocturnal boundary layer.     

Study of the Relationship of Distant SO2 Emissions to Dallas-Fort Worth Winter Haze

ABSTRACT

A study was conducted to estimate the changes in wintertime visual air quality in Dallas-Fort Worth (DFW) that might occur due to proposed reductions in SO₂ emissions at two steam electric generating plants in eastern Texas, each over 100 km from the city. To provide information for designing subsequent investigations, the haze was characterized broadly during the first year of the study. Meteorological data acquired then demonstrated that, during haze episodes, emissions from only one of the two plants were likely to be transported directly to DFW. Therefore, the second year of the study was centered on just one of the power plants. Air quality was then characterized within the urban area and at rural locations that would be upwind and downwind of the plant during transport to DFW. An instrumented aircraft measured plume dispersion and the air surrounding the plume on selected days. A mathematical model was used to predict the change that would occur in airborne particulate matter concentrations in DFW if SO₂ emissions were reduced to reflect the proposed limitations. The contribution of particles in the atmosphere to light extinction was estimated, and simulated photographs were produced to illustrate the visibility changes. The study concluded that the proposed emission reductions would, at most, subtly change perceived wintertime visibility.     

Dispersion of Traffic and Space Heating Emissions In Urban Settings

A long-term dispersion model is presented for traffic and space heating emissions in urban areas, allowing fast assessment of the spatial-averaged and center-maximum pollutant concentrations.

The assumption of study areas with circular shape and normal emissions density profiles is made for the purpose of streamlining model inputs with the inventory data normally available. In addition, the rather typical assumptions of Gaussian dispersion, narrow plume, flat or gently rolling terrain, homogeneous wind field and nonreactive pollutants are made. Values of σz from Briggs correlation are used with an initial value of 30 to account for building effects.

Meterological data inputs are reduced to six parameters, inventory data inputs to two, while computations are simplified to a degree that use of a digital computer is not required.

The model is well suited to yield separate assessments for individual types of sources and control measures, as well as to reveal sensitivities from parameters such as city size, or emission density levels and distribution patterns. Its predictions are virtually identical to those of the CDM-2 UNAPMAR model for study areas with circular shape and normal emissions density profiles, and as results do not appear overly sensitive to shape and distribution patterns, the model is believed to be valid for most urban areas.     

Assessing the representativeness of monitoring data from an urban intersection site in central London,UK

The wind flow field around urban street-building configurations has an important influence on the microscale pollutant dispersion from road traffic, affecting overall dilution and creating localised spatial variations of pollutant concentration. As a result, the “representativeness” of air quality measurements made at different urban monitoring sites can be strongly dependent on the interaction of the local wind flow field with the street-building geometry surrounding the monitor. The present study is an initial attempt to develop a method for appraising the significance of air quality measurements from urban monitoring sites, using a general application computational fluid dynamics (CFD) code to simulate small-scale flow and dispersion patterns around real urban building configurations. The main focus of the work was to evaluate routine CO monitoring data collected by Westminster City Council at an intersection of street canyons at Marylebone Road, Central London. Many monitors in the UK are purposely situated at urban canyon intersections, which are thought to be local “hot spots” of pollutant emissions, however very limited information exists in the literature on the flow and dispersion patterns associated with them. With the use of simple CFD simulations and the analysis of available monitoring data, it was possible to gain insights into the effect of wind direction on the small-scale dispersion patterns at the chosen intersection, and how that can influence the data captured by a monitor. It was found that a change in wind direction could result in an increase or decrease of monitored CO concentration of up to 80%, for a given level of traffic emissions and meteorological conditions. Understanding and de-coupling the local effect of wind direction from monitoring data using the methods presented in this work could prove a useful new tool for urban monitoring data interpretation.     

Air intake contamination by building exhausts: tracer gas investigation of atmospheric dispersion models in the urban environment

The establishment of a safe distance between sources of pollution and air intakes is based on a complex exercise that should take into account several wind, physical, and topographical factors. To estimate the maximum concentrations of the pollutants as a function of the distance from the emission source, some heating, ventilation, and air conditioning (HVAC) system designers use the atmospheric dispersion models suggested by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). Two of these models, the Halitsky and Wilson-Chui-Lamb models, have been developed and evaluated mainly with laboratory data. There have been relatively few evaluations with full-scale field data. The objective of this study, carried out on a building in downtown Montreal, Quebec, Canada, was to compare the measured concentrations of a tracer gas emitted by an exhaust stack with those predicted by these models. The results indicate that the Halitsky model gives lower than actual dilution, while the Wilson-Chui-Lamb model generally gives acceptable estimates, with occasional over-estimations of the dilution.