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.     

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.     

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.     

Nomograms for calculating pollution within street canyons

The Environment Act 1995 has introduced the notion of local air quality management which requires that air quality in towns be reviewed and assessed. There is a need to identify those streets that are worst affected by vehicular pollutants. Such worst cases are likely to be narrow congested streets with tall buildings on each side. A nomogram presented here allows rapid screening of pollution in congested street canyons. The strong dependence on wind direction is reduced to the two extremes, namely wind along and wind across the canyon. Then canyon concentrations are estimated according to street geometry and traffic flow. The nomogram is designed for use by local authorities, is quick and easy to use, and paper or computer versions are available. It is suggested that detailed monitoring or modelling may only be required when simple screening methods predict high air pollution.     

Screening and Scenarios of Traffic Emissions at Trier,Germany

SCOPE AND BACKGROUND: In the course of the European Council Directive on permissible air pollutant limit values, valid starting from 2005 there is an urgent call for action, particularly for fine dust (PM10). Current investigations (Junk & Helbig 2003, Reuter & Baumüller 2003) show that the limit values in certain places in congested areas are exceeded. Only if it is possible to locate these Hot Spots purposeful measures to reduce the ambient air pollution can be conducted. For an efficient identification of these Hot Spots numerical computer models or establishing special measurements networks are too expensive. Using the statistical model STREET 5.0 (KTT 2003) a cost-effective screening of the air pollution situation caused by the traffic can be done. METHODS: STREET is based on the 3-dimensional micro-scale non-hydrostatic flow- and dispersion model MISCAM (Eichhorn 1989). The results of over 100.000 different calculations with MISCAM are stored in a Database and used to calculate the emissions with STREET. In collaboration with the city council of Trier more than 150 streets were investigated, mapped, and calculated. A special urban climate measuring network supplies the necessary meteorological input data about the wind field and precipitation events in the valley of the Moselle. Information about road width and road orientation as well as building density was derived from aerial photographs. Traffic censuses and mobile air pollutants measurements supplied the remaining input data. We calculated the mean annual air pollutant concentrations for NO2, CO, SO2, O3, benzene as well as PM10. RESULTS: A comparison of the model results with the values obtained from the stations of the central emission measuring network of Rhineland-Palatinate (ZIMEN, annual report 2002) shows very good agreements. The model was not only used to calculate the annual air pollutant but also for urban planning and management. The absolute level of the air pollutant is mainly dependent on the amount of traffic in the street canyons. Therefore four different case-scenarios with varying quantity of traffic were calculated and interpreted for each street. The results of the calculation show that on the basis of the mean values for both NO2 and benzene, it is not to be expected that the limits PERSPECTIVES: Furthermore the model can be used to find the maximum tolerable numbers of cars for a street without exceeding the air pollutant thresholds.     

Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling

In order to carry out efficient traffic and air quality management, validated models and PM emission estimates are needed. This paper compares current available emission factor estimates for PM₁₀ and PM_2.5 from emission databases and different emission models, and validates these against eight high quality street pollution measurements in Denmark, Sweden, Germany, Finland and Austria.The data sets show large variation of the PM concentration and emission factors with season and with location. Consistently at all roads the PM₁₀ and PM_2.5 emission factors are lower in the summer month than the rest of the year. For example, PM₁₀ emission factors are in average 5–45% lower during the month 6–10 compared to the annual average.The range of observed total emission factors (including non-exhaust emissions) for the different sites during summer conditions are 80–130 mg km⁻¹ for PM₁₀, 30–60 mg km⁻¹ for PM_2.5 and 20–50 mg km⁻¹ for the exhaust emissions.We present two different strategies regarding modelling of PM emissions: (1) For Nordic conditions with strong seasonal variations due to studded tyres and the use of sand/salt as anti-skid treatment a time varying emission model is needed. An empirical model accounting for these Nordic conditions was previously developed in Sweden. (2) For other roads with a less pronounced seasonal variation (e.g. in Denmark, Germany, Austria) methods using a constant emission factor maybe appropriate. Two models are presented here.Further, we apply the different emission models to data sets outside the original countries. For example, we apply the “Swedish” model for two streets without studded tyre usage and the “German” model for Nordic data sets. The “Swedish” empirical model performs best for streets with studded tyre use, but was not able to improve the correlation versus measurements in comparison to using constant emission factors for the Danish side. The “German” method performed well for the streets without clear seasonal variation and reproduces the summer conditions for streets with pronounced seasonal variation. However, the seasonal variation of PM emission factors can be important even for countries not using studded tyres, e.g. in areas with cold weather and snow events using sand and de-icing materials. Here a constant emission factor probably will under-estimate the 90-percentiles and therefore a time varying emission model need to be used or developed for such areas.All emission factor models consistently indicate that a large part (about 50–85% depending on the location) of the total PM₁₀ emissions originates from non-exhaust emissions. This implies that reduction measures for the exhaust part of the vehicle emissions will only have a limited effect on ambient PM₁₀ levels.     

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.     

街道峡谷机动车尾气污染扩散模拟与影响因子分析研究

为预测和分析街道峡谷污染物浓度,研究了街道峡谷污染物浓度影响因子.利用重庆市交通干线街道峡谷两侧NOx浓度的监测数据,验证了街道峡谷机动车尾气污染扩散模型--OSPM模型.风速转换系数修正后的OSPM模型的模拟值与实测值的R达0.862 58;风场因子验证了风速转换系数修正后的OSPM模型能较好地模拟重庆市街道峡谷的污染物浓度,一定程度上能满足环境空气质量评价要求.同时,通过分析OSPM模型的影响因子,提出了控制街道峡谷机动车尾气污染状况的建议.     

Assessment of traffic-related air pollution in the urban streets before and during the 2008 Beijing Olympic Games traffic control period

In order to investigate the air quality and the abatement of traffic-related pollution during the 2008 Olympic Games, we select 12 avenues in the urban area of Beijing to calculate the concentrations of PM₁₀, CO, NO₂ and O₃ before and during the Olympic traffic controlling days, with the OSPM model.Through comparing the modeled results with the measurement results on a representative street, the OSPM model is validated as sufficient to predict the average concentrations of these pollutants at street level, and also reflects their daily variations well, i.e. CO presents the similar double peaks as the traffic flow, PM₁₀ concentration is influenced by other sources. Meanwhile, the model predicts O₃ to stay less during the daytime and ascend in the night, just opposite to NO₂, which reveals the impact of photochemical reactions. In addition, the predicted concentrations on the windward side often exceed the leeward side, indicating the impact of the special street shape, as well as the wind.The comparison between the predicted street concentrations before and during the Olympic traffic control period shows that the overall on-road air quality was improved effectively, due to the 32.3% traffic flow reduction. The concentrations of PM₁₀, CO and NO₂ have reduced from 142.6 μg m⁻³, 3.02 mg m⁻³ and 118.7 μg m⁻³ to 102.0 μg m⁻³, 2.43 mg m⁻³ and 104.1 μg m⁻³. However, the different pollutants show diverse changes after the traffic control. PM₁₀ decreases most, and the reduction effect focusing on the first half-day even clears the morning peak, whereas CO and NO₂ have even reductions to minify the daily fluctuations on the whole. Opposite to the other pollutants, ozone shows an increase of concentration. The average reduction rate of PM₁₀, CO, NO₂ and O₃ are respectively 28%, 19.3%, 12.3% and −25.2%. Furthermore, the streets in east, west, south and north areas present different air quality improvements, probably induced by the varied background pollution in different regions around Beijing, along with the impact of wind force. This finding suggests the pollution control in the surrounding regions, not only in the urban area.     

SIMAIR—Evaluation tool for meeting the EU directive on air pollution limits

Almost all Swedish cities need to determine air pollution levels—especially PM10—close to major streets. SIMAIR is an internet tool that can be used by all Swedish municipalities to assess PM10, NO₂, CO and benzene levels and how they compare to the EU directive. SIMAIR is delivered to the municipalities with all required input data pre-loaded and is meant to be used prior to decisions if and where, monitoring campaigns are required. The system includes a road and vehicle database with emission factors and a model to calculate non-tailpipe PM10 emissions. Regional and urban background contributions are pre-calculated and stored as hourly values on a 1×1 km² grid. The local contribution is calculated by the user, selecting either an open road or a street canyon environment.A comparison between measured and simulated concentrations in four street locations shows that SIMAIR is able to calculate statistics of yearly mean values, 90-percentile and 98-percentile daily mean values and the number of days exceeding the limit value that are well within ±50% that EU requires for model estimates of yearly mean values. In comparison, all values except one are within ±25% which is the quality objective for fixed measurements according to the EU directive.The SIMAIR model system is also able to separate the percentual contribution of the long-range transport from outside the city, the city contribution and the local contribution from the traffic of an individual street.     

Assessment of traffic-related air pollution in two street canyons in Paris: implications for exposure studies

The small-scale spatial variability of air pollution observed in urban areas has created concern about the representativeness of measurements used in exposure studies. It is suspected that limit values for traffic-related pollutants may be exceeded near busy streets, although respected at urban background sites. In order to assess spatial concentration gradients and identify weather conditions that might induce air pollution episodes in urban areas, different sampling and modelling techniques were studied.Two intensive monitoring campaigns were carried out in typical street canyons in Paris during winter and summer. Steep cross-road and vertical concentration gradients were observed within the canyons, in addition to large differences between roadside and background levels. Low winds and winds parallel to the street axis were identified as the worst dispersion conditions. The correlation between the measured compounds gave an insight into their sources and fate. An empirical relationship between CO and benzene was established. Two relatively simple mathematical models and an algorithm describing vertical pollutant dispersion were used. The combination of monitoring and modelling techniques proposed in this study can be seen as a reliable and cost-effective method for assessing air quality in urban micro-environments. These findings may have important implications in designing monitoring studies to support investigation on the health effects of traffic-related air pollution.     

Evaluating sources of indoor air pollution

Evaluation of indoor air pollution problems requires an understanding of the relationship between sources, air movement, and outdoor air exchange. Research is underway to investigate these relationships. A three-phase program is being implemented: 1) Environmental chambers are used to provide source emission factors for specific indoor pollutants; 2) An IAQ (Indoor Air Quality) model has been developed to calculate indoor pollutant concentrations based on chamber emissions data and the air exchange and air movement within the indoor environment; and 3) An IAQ test house is used to conduct experiments to evaluate the model results. Examples are provided to show how this coordinated approach can be used to evaluate specific sources of indoor air pollution. Two sources are examined: 1) para-dichlorobenzene emissions from solid moth repellant; and 2) particle emissions from unvented kerosene heaters. The evaluation process for both sources followed the three-phase approach discussed above. Para-dichlorobenzene emission factors were determined by small chamber testing at EPA's Air and Energy Engineering Research Laboratory. Particle emission factors for the kerosene heaters were developed in large chambers at the J. B. Pierce Foundation Laboratory. Both sources were subsequently evaluated in EPA's IAQ test house. The IAQ model predictions showed good agreement with the test house measurements when appropriate values were provided for source emissions, outside air exchange, in-house air movement, and deposition on "sink" surfaces.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Comparative study of measured and modelled number concentrations of nanoparticles in an urban street canyon

This study presents a comparison between measured and modelled particle number concentrations (PNCs) in the 10–300 nm size range at different heights in a canyon. The PNCs were modelled using a simple modelling approach (modified Box model, including vertical variation), an Operational Street Pollution Model (OSPM) and Computational Fluid Dynamics (CFD) code FLUENT. All models disregarded any particle dynamics. CFD simulations have been carried out in a simplified geometry of the selected street canyon. Four different sizes of emission sources have been used in the CFD simulations to assess the effect of source size on mean PNC distributions in the street canyon. The measured PNCs were between a factor of two and three of those from the three models, suggesting that if the model inputs are chosen carefully, even a simplified approach can predict the PNCs as well as more complex models. CFD simulations showed that selection of the source size was critical to determine PNC distributions. A source size scaling the vehicle dimensions was found to better represent the measured PNC profiles in the lowest part of the canyon. The OSPM and Box model produced similar shapes of PNC profile across the entire height of the canyon, showing a well-mixed region up to first ≈2 m and then decreasing PNCs with increased height. The CFD profiles do correctly reproduce the increase from road level to a height of ≈2 m; however, they do not predict the measured PNC decrease higher in the canyon. The PNC differences were largest between idealised (CFD and Box) and operational (OSPM) models at upper sampling heights; these were attributed to weaker exchange of air between street and roof-above in the upper part of the canyon in the CFD calculations. Possible reasons for these discrepancies are given.     

A spatial multicriteria model for determining air pollution at sample locations

Atmospheric pollution in urban centers has been one of the main causes of human illness related to the respiratory and circulatory system. Efficient monitoring of air quality is a source of information for environmental management and public health. This study investigates the spatial patterns of atmospheric pollution using a spatial multicriteria model that helps target locations for air pollution monitoring sites. The main objective was to identify high-priority areas for measuring human exposures to air pollutants as they relate to emission sources. The method proved to be viable and flexible in its application to various areas.

Implications:?Spatial multicriteria models provide a tool for air pollution management in urban areas. Analytic hierarchy process (AHP) modeling can help with the process of prioritizing monitoring site locations and minimizing costs.     

Screening Models for Estimating Toxic Air Pollution Near a Hazardous Waste Landfill

This paper is directed to environmental scientists concerned with assessing toxic air pollution downwind of hazardous waste landfills to determine whether potential health threats or exceedances of air quality standards exist. The purpose of this paper is to evaluate the performance of four air quality screening models.

The emission rate of vinyl chloride from the BKK co-disposal landfill in West Covina, California is estimated. Ambient vinyl chloride concentrations are estimated using a ground level point source model, two virtual point source models, arid the simple box model with meteorological and landfill input data representative of periods when ambient monitoring was conducted. The two virtual point source models are most precise and accurate in estimating 24-hour vinyl chloride concentrations. However, the results could include compensating errors in the emission rate and dispersion calculations because the emission rate estimate could not be independently evaluated.     

Predictions of U.K. regulated power station contributions to regional air pollution and deposition: a model comparison exercise

Contributions of the emissions from a U.K. regulated fossil-fuel power station to regional air pollution and deposition are estimated using four air quality modeling systems for the year 2003. The modeling systems vary in complexity and emphasis in the way they treat atmospheric and chemical processes, and include the Community Multiscale Air Quality (CMAQ) modeling system in its versions 4.6 and 4.7, a nested modeling system that combines long- and short-range impacts (referred to as TRACK-ADMS [Trajectory Model with Atmospheric Chemical Kinetics-Atmospheric Dispersion Modelling System]), and the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. An evaluation of the baseline calculations against U.K. monitoring network data is performed. The CMAQ modeling system version 4.6 data set is selected as the reference data set for the model footprint comparison. The annual mean air concentration and total deposition footprints are summarized for each modeling system. The footprints of the power station emissions can account for a significant fraction of the local impacts for some species (e.g., more than 50% for SO2 air concentration and non-sea-salt sulfur deposition close to the source) for 2003. The spatial correlation and the coefficient of variation of the root mean square error (CVRMSE) are calculated between each model footprint and that calculated by the CMAQ modeling system version 4.6. The correlation coefficient quantifies model agreement in terms of spatial patterns, and the CVRMSE measures the magnitude of the difference between model footprints. Possible reasons for the differences between model results are discussed. Finally, implications and recommendations for the regulatory assessment of the impact of major industrial sources using regional air quality modeling systems are discussed in the light of results from this case study.     

Modelling dispersion of traffic pollution in a deep street canyon: Application of CFD and operational models

In this study, numerical modelling of the flow and concentration fields has been undertaken for a deep street canyon in Naples (Italy), having aspect ratio (i.e. ratio of the building height H to the street width W) H/W = 5.7. Two different modelling techniques have been employed: computational fluid dynamics (CFD) and operational dispersion modelling. The CFD simulations have been carried out by using the RNG k–? turbulence model included in the commercial suite FLUENT, while operational modelling has been conducted by means of the WinOSPM model. Concentration fields obtained from model simulations have been compared with experimental data of CO concentrations measured at two vertical locations within the canyon. The CFD results are in good agreement with the experimental data, while poor agreement is observed for the WinOSPM results. This is because WinOSPM was originally developed and tested for street canyons with aspect ratio H/W ≌ 1. Large discrepancies in wind profiles simulated within the canyon are observed between CFD and OSPM models. Therefore, a modification of the wind profile within the canyon is introduced in WinOSPM for extending its applicability to deeper canyons, leading to an improved agreement between modelled and experimental data. Further development of the operational dispersion model is required in order to reproduce the distinct air circulation patterns within deep street canyons.     

Assessment of vehicular pollution in China

As the motor vehicle population in China continues to increase at an annual rate of approximately 15%, air pollution related to vehicular emissions has become the focus of attention, especially in large cities. There is an urgent need to identify the severity of this pollution in China. Based on an investigation into vehicle service characteristics, this study used a series of driving cycle tests of in-use Chinese motor vehicles for their emission factors in laboratories, which indicated that CO and HC emission factors are 5-10 times higher, and NOx 2-5 times higher, than levels in developed countries. The MOBILE5 model was adapted to the Chinese situation and used to calculate the emission of pollutants from motor vehicles. Results show that vehicle emission is concentrated in major cities, such as Beijing, Guangzhou, Shanghai, and Tianjin. Motor vehicle emissions contribute a significant proportion of pollutants in those cities, with contribution rates of CO and NOx greater than 80% and 40%, respectively, in Beijing and Guangzhou. Urban air quality is far worse than the national ambient air quality standard. In conclusion, although China has a relatively small number of motor vehicles, most of them are concentrated within metropolitan areas, and their emissions are closely related to urban air pollution problems in large cities.     

Development of the typical driving cycle for buses in Hanoi,Vietnam

This paper develops a typical driving cycle for buses in Hanoi that does not require the deconstruction of the natural driving patterns. Real velocity–time data were collected along 15 routes in the inner city. The raw velocity–time series were preprocessed to remove errors, and smooth and denoise the data. These data, then, were tested for stationary behavior before being used in the construction of the driving cycle based on Markov chain theory. The 14 representative parameters of the driving cycle, including vehicle-specific power, which were extracted from 33 driving cycle parameters using the hierarchical agglomerative clustering method, were used to integrate the features of realistic driving patterns into the typical driving cycle. The conformity of the developed driving cycle with the real-world driving data was evaluated by the speed–acceleration frequency distribution (SAFD). A typical driving cycle for buses in Hanoi with a SAFD of 13.2% was developed. This is the first driving cycle developed for buses in Vietnam.

Implications: A typical driving cycle was developed for the first time for buses in Hanoi. With the deviation in speed-acceleration frequency distribution (SAFD) reaching to 13.2%, the developed driving cycle reflects well the overall real-world driving data in the city. This driving cycle, therefore, can be applied for the development of the country-specific emission factors and emission inventories for buses which are a very good tool as well as useful information for integrated air quality management in Hanoi.