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.     

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.     

Estimation of road traffic emission factors from a long term tracer study

Road traffic emissions, one of the largest source categories in megacity inventories, are highly uncertain. It is essential to develop methodologies to reduce these uncertainties to manage air quality more effectively. In this paper, we propose a methodology to estimate road traffic emission factors (EFs) from a tracer experiment and from roadside pollutants measurements. We emitted continuously during about 300 non-consecutive hours a passive tracer from a finite line source placed on one site of an urban street. At the same time, we measured continuously the resulting tracer concentrations at the other side of the street with a portable on-line gas chromatograph. We used n-propane contained in commercial liquid petroleum gas (LPG) as a passive tracer. Propane offers several advantages to traditional tracers (SF6, N2O, CFCs): low price, easily available, non-reactive, negligible global warming potential, and easy to detect with commercial on-line gas chromatographs.The tracer experiment was carried out from January to March 2007 in a busy street of Ho Chi Minh City (Vietnam). Traffic volume, weather information and pollutant concentrations were also measured at the measurement site. We used the results of the tracer experiment to calculate the dilution factors and afterwards we used these dilution factors, the traffic counts and the pollutant concentrations to estimate the EFs. The proposed method assumes that the finite emission line represents the emission produced by traffic in the full area of the street and therefore there is an error associated to this assumption. We use the Computational Fluids Dynamics (CFD) model MISKAM to calculate this error and to correct the HCMC EFs. EFs for 15 volatile organic compounds (VOCs) and NO are reported here. A comparison with available studies reveals that most of the EFs estimated here are within the range of EFs reported in other studies.     

Urban atmospheric pollution: personal exposure versus fixed monitoring station measurements

We initiated the PETER (pedestrian environmental traffic pollutant exposure research) project to investigate pedestrians' exposure to traffic related atmospheric pollutants, based on data obtained with the collaboration of selected categories of pedestrian urban workers. We investigated relations between roadside personal exposure levels of volatile aromatic hydrocarbons (including benzene) and particulate matter <10 microm (PM10) among traffic police (n = 126) and parking wardens (n = 50) working in downtown Bologna, Italy. Data were collected from workshifts throughout four 1-week periods in different seasons of 2000-2001. For benzene and PM10, comparisons were made with measurements by fixed monitoring stations, and influence of localized traffic intensity and meteorological parameters was examined. Roadside personal exposure to benzene correlated more strongly with other volatile aromatic hydrocarbons (toluene, xylenes and ethylbenzene) than with PM10. Benzene and PM10 personal exposure levels were higher than fixed monitoring station values (both p<0.0001). At multivariate analysis, benzene and PM10 data from fixed monitoring stations both correlated with meteorological variables, and were also influenced by localized traffic intensity. Plausibly because of the downtown canyon-like streets, weather conditions (during a period of drought) only marginally affected benzene personal exposure, and moderately affected PM10 personal exposure. These findings reinforce the concept that urban atmospheric pollution data from fixed air monitoring stations cannot automatically be taken as indications of roadside exposures.     

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

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

Air pollution modeling at road sides using the operational street pollution model--a case study in Hanoi, Vietnam

In many metropolitan areas, traffic is the main source of air pollution. The high concentrations of pollutants in streets have the potential to affect human health. Therefore, estimation of air pollution at the street level is required for health impact assessment. This task has been carried out in many developed countries by a combination of air quality measurements and modeling. This study focuses on how to apply a dispersion model to cities in the developing world, where model input data and data from air quality monitoring stations are limited or of varying quality. This research uses the operational street pollution model (OSPM) developed by the National Environmental Research Institute in Denmark for a case study in Hanoi, the capital of Vietnam. OSPM predictions from five streets were evaluated against air pollution measurements of nitrogen oxides (NO(x)), sulfur dioxide (SO2), carbon monoxide (CO), and benzene (BNZ) that were available from previous studies. Hourly measurements and passive sample measurements collected over 3-week periods were compared with model outputs, applying emission factors from previous studies. In addition, so-called "backward calculations" were performed to adapt the emission factors for Hanoi conditions. The average fleet emission factors estimated can be used for emission calculations at other streets in Hanoi and in other locations in Southeast Asia with similar vehicle types. This study also emphasizes the need to further eliminate uncertainties in input data for the street-scale air pollution modeling in Vietnam, namely by providing reliable emission factors and hourly air pollution measurements of high quality.     

Variability of Nox and No2 concentrations observed at pedestrian level in the city centre of a medium sized urban area

NO_x and NO₂ concentrations were measured at different locations in a city centre of an urban zone (Population 450 000) in order to study the variation of the outdoor exposure at pedestrian level. These measurements were carried out to understand the influence of traffic emissions at each measured site. The observations were done during four weeks in winter, including several days with high pollution levels. The results at different locations have been used to analyse criteria recommended for locating observation sites in a monitoring network. No large differences in background pollution averaged over several weeks have been found throughout the city centre, even during pollution peaks. Measurements were also carried out inside one street canyon. The contribution of the street traffic to the NO=NO_x−NO₂ concentrations observed at side-walk has been found important, i.e., several times the background level. On the other hand, the majority of observed NO₂ pollution is due to the contribution of background pollution within the street. The pollutant excess at pedestrian level is strongly correlated to the street traffic emission and to the atmospheric turbulence observed at roof level. Application of a box model to the street data demonstrates that such models can be useful to estimate the pollutant accumulation within the street.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Evaluation of traffic-producing turbulence schemes within Operational Street Pollution Models using roadside measurements

Low wind scenarios are associated with the worst air pollution episodes in urban street canyons. Under these conditions, operational dispersion models often over-predict pollutant concentration. Traffic-producing turbulence (TPT) becomes dominant in mixing and diluting traffic-related pollutants under low wind speed conditions. Determining the TPT effect on the flow and dispersion patterns within urban street canyons is crucial for the development of detailed operational dispersion models for assessing urban air quality. Several spatially averaged TPT formulations have been recently proposed in the literature. However, only a few attempts have been made so far to incorporate different TPT schemes into operational dispersion models and evaluate their performance using measurements.In this paper, several TPT schemes presented in literature were evaluated. Two TPT schemes were implemented in the well-validated Windows version of the Danish Operational Street Pollution Model (WinOSPM). Both formulations were evaluated using six independent datasets of roadside CO concentrations collected in European cities. Statistical and sensitivity analyses were undertaken to test the performance of the different formulations. The results showed that the overall model performance was significantly sensitive to the TPT schemes adopted. The model performance improved when a detailed characterisation of the TPT, depending on the density of road traffic, was used.     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

A Wind Tunnel Study of Gaseous Pollutants in City Street Canyons

Steady state mean concentrations of tracer gas were measured in a 400:1 scale model of an idealized city with variable geometry placed within a wind tunnel at various orientations to the mean flow for a free stream velocity of 6.8 ft/sec. The tracer gas was released from two parallel line sources to simulate lanes of traffic in an effort to quantify the persistence of pollution as well as the mean values realized at street levels. An aerodynamically rough turbulent boundary layer of neutral thermal stratification was employed to simulate the atmosphere. Values of concentration measured in the model city were converted to prototype concentrations in ppm and compared to National Ambient Air Quality Standards. It was shown that single isolated structures may cause favorable mixing of pollution downwind but very high concentrations exist in the immediate leeward vicinity of the building. Two favorable geometries for city blocks tested were found to reduce pedestrian exposure to pollution both near heavy traffic congestion and downwind. It was concluded that the pollutant dilution was controlled by the mean flow rather than by turbulent diffusion and that the lateral spread of the plume was slight as one proceeded downwind of the line source. The combination of favorable geometry and higher dilution velocities may bring pollution levels down to existing Air Quality Standards. The body of information presented in this paper should interest city planners and air quality monitoring personnel, as well as those researchers attempting to study and model flow in city street canyons. It provides order of magnitude estimates on pedestrian and office worker exposure to pollutants under a wide range of conditions.     

A statistical assessment of saturation and mobile sampling strategies to estimate long-term average concentrations across urban areas

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998-2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO2, PM10 and NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Airborne pollutants along a roadside: assessment using snow analyses and moss bags

Vertical snow sampling and moss bag transplants were used to estimate the local inorganic and organic pollutant load deposited from traffic along a major highway in Finland. The pH and concentrations of Cl(-), NO(3)(-), SO(4)(2-), Ca(2+), Na(+) and polyaromatic hydrocarbons (PAHs) were determined from snow samples collected in winter at different sites along the highway. In summer, moss bags containing 20 g of fresh red-stemmed feather moss (Pleurozium schreberi) were transplanted at the same sites. The moss bag transplants remained exposed to roadside traffic for a period of one month following which the samples were collected and the PAH profiles and concentrations were analysed. The deposition of inorganic and organic pollutants from road traffic was observed up to 60 m from the road. The prevailing winds had a significant effect on the dispersion of pollutants. Snow appears to be a good collector of inorganic pollutants from the atmosphere and can be used to monitor local airborne pollution from road traffic. Snow packs can also be used as passive collectors of organic pollutant loads from road traffic on a local scale. To monitor organic PAH deposition from the road traffic, moss bags appeared to be better indicators compared to snow sampling. The efficiency of moss bags in accumulating PAH compounds indicate that vegetation may be an important sink for traffic pollution.     

Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility

As part of the Southern Appalachian Mountains Initiative, a comprehensive air quality modeling system was developed to evaluate potential emission control strategies to reduce atmospheric pollutant levels at the Class I areas located in the Southern Appalachian Mountains. Six multiday episodes between 1991 and 1995 were simulated, and the skill of the modeling system was evaluated. Two papers comprise various parts of this study. Part I details the ozone model performance and the methodology that was used to scale discrete episodic pollutant levels to seasonal and annual averages. This paper (part II) addresses issues involved with modeling particulate matter (PM) and its relationship to visibility. For most of the episodes, the fractional error was approximately 50% or less for the major constituents of the fine PM (i.e., sulfate [SO4] and organics) in the region. The mean normalized errors and fractional errors are generally larger for the NO3 and soil components, but these components are relatively small. Variations in modeling bias with pollutant levels were also examined. The model showed a systematic overestimation for low levels and an underestimation for high levels for most PM species. For ammonium, the model showed better performance at lower SO4 concentrations when the measured SO4 was assumed to be completely neutralized (ammonium sulfate) and better performance at higher SO4 concentrations when the partially neutralized (ammonium bisulfate) assumption was made. The contributions of various components of PM to reductions in visibility were also calculated; SO4 was found to be the major contributor.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

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.     

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.     

北京市交通道路空气中NOx的污染现状及时空变化规律研究

基于2008年及2009年分4个季节对北京市3种类型道路（开阔型、交叉路口型和峡谷型）空气中的NOx的现场监测结果,分析了3种类型道路空气中NOx的污染现状和时空变化规律及影响因素。实验结果表明,昼间北京市各类型街道空气中NOx浓度呈早晚浓度高、中午浓度低的变化规律,NOx浓度随季节和车流量变化较明显。交通道路空气中NO占NOx的分担率高,且有较好的相关性,而NO2分担率较低,与NOx相关性较差。     

PM10 emission factors for non-exhaust particles generated by road traffic in an urban street canyon and along a freeway in Switzerland

Recent studies have shown clear contributions of non-exhaust emissions to the traffic related PM10 load of the ambient air. These emissions consist of particles produced by abrasion from brakes, road wear, tire wear, as well as vehicle induced resuspension of deposited road dust. The main scope of the presented work was to identify and quantify the non-exhaust fraction of traffic related PM10 for two roadside locations in Switzerland with different traffic regimes. The two investigated locations, an urban street canyon with heavily congested traffic and an interurban freeway, are considered as being typical for Central Europe. Mass-relevant contributions from abrasion particles and resuspended road dust mainly originated from particles in the size range 1–10 μm. The results showed a major influence of vehicle induced resuspension of road dust. In the street canyon, the traffic related PM10 emissions (LDV: 24 ± 8 mg km^?1 vehicle^?1, HDV: 498 ± 86 mg km^?1 vehicle^?1) were assigned to 21% brake wear, 38% resuspended road dust and 41% exhaust emissions. Along the freeway (LDV: 50 ± 13 mg km^?1 vehicle^?1, HDV: 288 ± 72 mg km^?1 vehicle^?1), respective contributions were 3% brake wear, 56% resuspended road dust and 41% exhaust emissions. There was no indication for relevant contributions from tire wear and abrasion from undamaged pavements.