道路交通噪声预测的研究进展

为评价道路交通噪声影响情况,以美国联邦公路管理局(FHWA)噪声预测模型为主,各国相继开发了基于当地实际情况的道路交通噪声预测模型,中国也以导则和规范等形式相继发布了各种交通噪声预测模型。中国进行噪声环境影响评价中,用得较多的主要有《环境影响评价技术导则声环境》(HJ 2.4—2009)、《公路建设项目环境影响评价规范》(JTG B03—2006)推荐的噪声预测模型,此外也有部分评价工作采用了德国的Cadna A软件。通过对比分析,HJ 2.4—2009的衰减及修正因素在综合考虑FH-WA噪声预测模型及JTG B03—2006基础上更加全面,而JTG B03—2006和Cadna A软件在源强和车速确定方面则均较成熟。有必要根据区域道路特点,选择适合特征区域的道路交通噪声预测模型,并结合实际情况对模型参数进行合理修正,最终形成一些可供区域参考的统一的模型修正参数,积极推动中国的声环境评价工作的发展。     

高架复合道路噪声声场分布研究

高架复合道路有效地缓解了交通拥挤的问题，但随之也带来了严重的噪声污染，以几何声学和衍射声学为理论基础，利用声级叠加原理，建立了高架复合道路噪声对临街建筑立面影响的预测模式。预测值与实测值基本相符，可直接应用于城市噪声预测。为城市发展规划尤其是城市高架复合道路的发展提供了科学依据。     

Traffic noise exposure of high-rise residential buildings in urban area

Noise pollution is a major factor of environmental complaints in many cities, which has significant impacts on human health. As a dominating source of environmental noise, the impact of road traffic noise is increasing. Residents living in high-rise buildings along the main road are severely affected by traffic noise. In order to assess the noise level of urban area along the main road in Guangzhou, three buildings were selected to conduct traffic noise measurements, and the questionnaire about traffic noise impact on human being was completed. Through the questionnaire, around 70% of participants consider the traffic noise has negative effect, and about 60% of participants consider the noise has moderate or much higher impact on physical comfort. Around 65% of participants consider the noise had moderately or much higher impact on their psychological comfort. By analyzing the measured data, all of the measured noise levels in three buildings exceed the recommended limit of 55 dB (A) in the daytime and 45 dB (A) in the night for residence, and the exceeded value can be up to 16 dB (A). By comparing the fitting curve of noise level transfer function on each floor relative to the reference floor, the quadratic polynomial was selected to plot the transfer function rather than cubic polynomial.

     

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.     

Benefits of mitigated ambient air quality due to transportation control on childhood asthma hospitalization during the 2002 summer Asian games in Busan, Korea

The objective of this study is to see whether there were any health benefits of mitigated air pollution concentration due to reduced traffic flow during a citywide intervention for the 2002 Summer Asian Games. Relative risks of hospitalization for childhood asthma during the post-Asian Game period compared with the baseline period were estimated using a time-series analysis of the generalized additive Poisson model. Fourteen consecutive days of traffic volume control in Busan during the Games reduced all regulated air pollutant levels by 1-25%. The estimated relative risk of hospitalization during the post-Games period over the baseline period was 0.73 (95% confidence interval [CI] = 0.49, 1.11). We observed that this reduced air pollution was unique in 2002 when the traffic volume reduction program was applied during the Games period. This empirical data provides epidemiologic evidence of the health benefits resulting from environmental interventions to reduce ambient air pollution.     

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.     

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.     

Adaptive neuro-fuzzy based modelling for prediction of air pollution daily levels in city of Zonguldak

Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters in the urban area are important due to health impact. Artificial intelligent techniques are successfully used in modelling of highly complex and non-linear phenomena. In this study, adaptive neuro-fuzzy logic method has been proposed to estimate the impact of meteorological factors on SO2 and total suspended particular matter (TSP) pollution levels over an urban area. The model forecasts satisfactorily the trends in SO2 and TSP concentration levels, with performance between 75-90% and 69-80 %, respectively.     

Traffic congestion and ozone precursor emissions in Bilbao (Spain)

GOAL. SCOPE. BACKGROUND: In urban environments, the measured levels of ozone are the result of the interaction between emissions of precursors (mainly VOCs and NOx) and meteorological effects. In this work, time series of daily values of ozone, measured at three locations in Bilbao (Spain), have been built. Then, after removing meteorological effects from them, ozone and traffic data have been analyzed jointly. The goal was to identify traffic situations and link them to ozone levels in the area of Bilbao. METHODS: To remove meteorological effects from the selected ozone time series, the technique developed by Rao and Zurbenko was used. This is a widely used technique and, after its application, the fraction obtained from a given ozone time series represents an ozone forming capability attributable to emissions of precursors. This fraction is devoid of any meteorological influence and includes only the apportion of periodicities above 1.7 years. In the case of Bilbao, the ozone fractions obtained at three locations have been compared on that time scale with traffic data from the area. RESULTS AND DISCUSSION: For the 1993-1996 period, a regression analysis of the ozone and traffic fractions due to periodicities above 1.7 years (long-term fractions), shows that traffic is the main explanatory factor for ozone with R2 ranging from 0.916 to 0.996 at the three locations studied. Analysis of these longterm fractions has made it possible to identify two traffic regimes for the whole area, associated to different profiles of ozone forming capability. The first one favors low ozone forming capability, and is associated with a situation of fluent traffic. The second one shows high ozone forming capability and represents congestion. Joint analysis of raw data of ozone and traffic do not show any clear pattern due to the strong masking effects that seasonal-meteorological effects (mainly radiation) have on the measured ozone signal. If only immission data of ozone are available, as in this case, a comparison between ozone and traffic can only be made on the long-term time scale, since that is the only fraction embedded in the ozone time series that can exclusively be attributed to emissions of precursors. This fact stresses the need to study the different fractions embedded in the time series of ozone measured levels separately. CONCLUSION: Though the coefficients obtained in the regression are only valid for the 1993-1996 period, these traffic regimes represent long-term targets (congestion or fluent traffic) that can inspire policies for a joint management of the traffic and pollution by ozone in the area of Bilbao beyond that period. RECOMMENDATIONS AND OUTLOOK: The results of this work show the need of a joint management of ozone and traffic in Bilbao. Since an accurate knowledge of traffic was not available, the use of emission factors to relate traffic and actual ozone levels has not been possible. For this reason, this study has focused on the long-term fractions of traffic and ozone. In the future, if a more accurate knowledge of traffic is available, it will be possible to find relationships between traffic and ozone on all time scales.     

Oxidant stress, antioxidants and nitric oxide in traffic police of Hyderabad, India

Exposure to environmental pollutants is known to be harmful to health, in general, and to lungs in particular. In this respect, traffic police are at particular risk due to the nature of their job, since they are exposed to emissions from the vehicles. Here, we show that in the traffic police of Hyderabad city, India, the plasma levels of lipid peroxides are high, whereas the concentrations of the nitric oxide are low. In addition, the levels of various antioxidants in the RBC lysate such as catalase, superoxide dismutase and glutathione peroxidase were found to be low with no significant alteration in plasma ceruloplasmin levels. These results suggest that exposure to air pollutants, a major portion of which is due to emissions from the vehicles, can increase oxidant stress, decrease the levels of antioxidants and nitric oxide. This imbalance in the oxidant/antioxidant system may lead to lung damage and is likely to cause respiratory problems in individuals exposed to air pollution.     

Model for estimation of traffic pollutant levels in northern communities

Using models to estimate the contribution of traffic to air pollution levels from known traffic data typically requires the knowledge of model parameters such as emission factors and meteorological conditions. This paper presents a state-space model analysis method that does not require the knowledge of model parameters; these parameters are identified from measured traffic and ambient air quality data. This method was used to analyze carbon monoxide (CO) in downtown Fairbanks, AK, which is the community of focus for this paper. It was found that traffic contributed, on average, 53% to the total CO levels over the last six winters. The correlation coefficient between the measured and model-predicted daily profiles of the CO concentration was 0.98, and the results were in good agreement with earlier findings obtained via a thorough CO emission inventory. This justified the usability of the method and it was further used to analyze fine particulate matter (PM2.5) in downtown Fairbanks. It was found that traffic contributed, on average, approximately 30% to the total PM2.5 levels over the last six winters. The correlation coefficient between the measured and model-predicted daily profiles of the PM2.5 concentration was 0.98.     

Exploring the processes governing roadside pollutant concentrations in urban street canyon

This paper describes an in-depth analysis to investigate the huge variation in the measured roadside air-pollutant concentrations of carbon monoxide and nitrogen dioxide in terms of the traffic flow levels, the orientation of the street to the prevailing wind, the wind speed, temperature and barometric pressure. The work has attempted to develop generic parameters that can be applied to other urban areas. However, in the absence of a measure of congestion at the site in Palermo (Italy), the methodological approach proposed used the simultaneous noise measurements, in units of decibels (B), to help parameterise a generic congestion indicator in terms of the traffic flow. The potential transferability of the approach was demonstrated for a site in Marylebone Road, London (UK), given the similarity of the two study sites, canyon shape, traffic characteristics and road orientation. The results showed that, within the range of data available, noise levels could be used as a proxy for flow change on the shoulders of the peak hour and hence congestion and a generic relationship with factors statistically significant at 99 % confidence allows roadside concentrations due to traffic to be estimated with a regression coefficient of R ²?=?0.73 (R?=?0.85). The research demonstrates that whilst there are indeed underlying relationships that can explain the roadside concentrations based on traffic and meteorological conditions, evidence is presented that confirms the complexity of the physical and chemical processes that govern roadside concentrations.     

Determinants of perceived air pollution annoyance and association between annoyance scores and air pollution (PM2.5, NO2) concentrations in the European EXPOLIS study

Apart from its traditionally considered objective impacts on health, air pollution can also have perceived effects, such as annoyance. The psychological effects of air pollution may often be more important to well-being than the biophysical effects. Health effects of perceived annoyance from air pollution are so far unknown. More knowledge of air pollution annoyance levels, determinants and also associations with different air pollution components is needed. In the European air pollution exposure study, EXPOLIS, the air pollution annoyance as perceived at home, workplace and in traffic were surveyed among other study objectives. Overall 1736 randomly drawn 25–55-yr-old subjects participated in six cities (Athens, Basel, Milan, Oxford, Prague and Helsinki). Levels and predictors of individual perceived annoyances from air pollution were assessed. Instead of the usual air pollution concentrations at fixed monitoring sites, this paper compares the measured microenvironment concentrations and personal exposures of PM_2.5 and NO₂ to the perceived annoyance levels. A considerable proportion of the adults surveyed was annoyed by air pollution. Female gender, self-reported respiratory symptoms, downtown living and self-reported sensitivity to air pollution were directly associated with high air pollution annoyance score while in traffic, but smoking status, age or education level were not significantly associated. Population level annoyance averages correlated with the city average exposure levels of PM_2.5 and NO₂. A high correlation was observed between the personal 48-h PM_2.5 exposure and perceived annoyance at home as well as between the mean annoyance at work and both the average work indoor PM_2.5 and the personal work time PM_2.5 exposure. With the other significant determinants (gender, city code, home location) and home outdoor levels the model explained 14% (PM_2.5) and 19% (NO₂) of the variation in perceived air pollution annoyance in traffic. Compared to Helsinki, in Basel and Prague the adult participants were more annoyed by air pollution while in traffic even after taking the current home outdoor PM_2.5 and NO₂ levels into account.     

Validity of ambient levels of fine particles as surrogate for personal exposure to outdoor air pollution--results of the European EXPOLIS-EAS Study (Swiss Center Basel)

To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM2.5 total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated. Personal exposures to PM2.5 mass were not correlated to corresponding home outdoor levels (n = 44, rSpearman (Sp) = 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, rSp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, rSp = 0.53; Br: n = 44, rSp = 0.21) and crustal (Ca: n = 44, rSp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland. We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM2.5 levels may be more appropriate exposure estimates than total personal PM2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.     

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.     

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.     

The contribution of ship emissions to air pollution in the North Sea regions

As a consequence of the global distribution of manufacturing sites and the increasing international division of labour, ship traffic is steadily increasing and is becoming more and more important as an origin of air pollution.This study investigates the impact of ship emissions in coastal areas of the North Sea under conditions of the year 2000 by means of a regional chemistry transport model which runs on a sufficiently high resolution to study air pollution in coastal regions. It was found that northern Germany and Denmark in summer suffer from more than 50% higher sulphate, nitrate and ammonium aerosol concentrations due to contributions from ships. The implementation of a sulphur emission control area (SECA) in the North Sea, as it was implemented at the end of 2007, directly results in reduced sulphur dioxide and sulphate aerosol concentrations while nitrate aerosol concentrations are slightly increased.     

Distance-weighted traffic density in proximity to a home is a risk factor for leukemia and other childhood cancers

Occupational exposure to elevated concentrations of benzene is a known cause of leukemia in adults. Concentrations of benzene from motor vehicle exhaust could be elevated along highly trafficked streets. Several studies have reported significant associations between proximity to highly trafficked streets and the occurrence of childhood cancers and childhood leukemia. These associations may be due to chronic exposure to benzene or other carcinogenic components of vehicle exhaust from these nearby streets or to some other factor (e.g., noise, increased light exposure, or some unaccounted--for socioeconomic variable). We used data for homes studied in an earlier childhood cancer study conducted in Denver, CO, in the 1980s. No air pollution measurements were made in the original study. We identified the highest trafficked street near each study home and obtained the traffic density in 1979 and 1990. Traffic density was weighted for the distance from the street to the home using 3 different widths of Gaussian curves to approximate the decay of the emissions into the surrounding neighborhoods. The associations between the 750-ft-wide distance-weighted traffic density metrics and all childhood cancers and childhood leukemia are strongest in the highest traffic density category (> or = 20,000 vehicles per day [VPD]). The odds ratio is 5.90 (95% confidence interval [CI] 1.69-20.56) for all cancers and 8.28 (95% CI 2.09-32.80) for leukemia. The results are suggestive of an association between proximal high traffic streets with traffic counts > or = 20,000 VPD and childhood cancer, including leukemia.     

Prediction of Traffic Noise: A Screening Technique

Abstract

Traffic noise is ubiquitous in many communities and is an important environmental concern, especially for persons located near major roadways. Several different methods are available to estimate noise levels resulting from roadway traffic. These include computational, graphical, and computer modeling techniques.

The prediction methodology presented here is a simplified technique that can be used for estimating noise resulting from traffic and for screening traffic noise impacts. This Traffic Noise Screening (TNS) approach consists of a series of traffic noise level prediction graphs developed for different roadway configurations. The graphs are based on the results from using the Federal Highway Administration (FHWA) STAMINA2.0 computerized noise prediction model for various scenarios. Data inputs to the TNS approach include roadway geometries, traffic volumes, vehicle travel speed, and centerline distance to the receptors.

The TNS graphs allow easy estimation of traffic noise levels for use in predicting traffic-related noise impacts. This TNS approach is not intended as a substitute for detailed modeling, such as with STAMINA2.0, but as a screening tool to aid in determining when detailed modeling may be necessary. If screening results indicate that noise estimates are significant, or if the scenario is rather complex, then additional, more detailed modeling can be performed.     

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.