Remote sensing of PM, NO, CO and HC emission factors for on-road gasoline and diesel engine vehicles in Las Vegas, NV

A novel light detection and ranging-based remote sensing system was assembled and used to measure mass particulate matter (PM) emissions per unit of fuel burned from in-use on-road vehicles. A commercially available remote sensing system was concurrently used to measure emissions of carbon monoxide (CO), nitrogen oxide (NO) and hydrocarbons (HC). The two systems were used to measure 61,207 gasoline and 1180 diesel powered vehicle emissions in Las Vegas, NV from 4/4/2000 to 5/16/2002. Emission factors were related to vehicle age, weight class and fuel type by matching license IDs to the state registration data. Measurements of vehicle speed and acceleration permitted the analysis of emission factors by vehicle specific power (VSP). Average emission factors were calculated for light-duty (<3863 kg [8500 lbs]) gasoline vehicles (LDGV), light-duty diesel vehicles (LDDV), heavy-duty (>3863 kg [8500 lbs]) gasoline vehicles (HDGV) and heavy-duty diesel vehicles (HDDV). LDDV and HDDV emitted approximately 25 times more PM per mass of fuel than LDGV and HDGV. Sufficient numbers of LDGV were measured to relate VSP with CO, HC and NO emissions. No relationship was observed between PM emissions and VSP. PM emission factors from LDGV increased with vehicle age. Fuel-based emission factors measured by remote sensing were compared with MOBILE6 and PART5 emissions model factors. Good agreement was observed for HC emission factors for vehicles less than 20 years old. MOBILE6 CO emission factors were approximately 2 times greater than measured CO emission factors for vehicles less than 13 years old. Measured NO emission factors were approximately 50% greater than MOBILE6 factors for vehicles 7-15 years old but in good agreement for vehicles less than 7 years old. Measured PM emission factors showed a clear increase with vehicle age, however, PART5 uses only a single PM emission factor for LDGV less than 18 years old. The PM emission factors for the fleet of LDGV, HDGV, LDDV and HDDV were 0.06, 0.05, 1.6 and 1.5 g/kg, respectively.     

High resolution modeling of the effects of alternative fuels use on urban air quality: Introduction of natural gas vehicles in Barcelona and Madrid Greater Areas (Spain)

The mitigation of the effects of on-road traffic emissions on urban air pollution is currently an environmental challenge. Air quality modeling has become a powerful tool to design environment-related strategies. A wide range of options is being proposed; such as the introduction of natural gas vehicles (NGV), biofuels or hydrogen vehicles. The impacts on air quality of introducing specific NGV fleets in Barcelona and Madrid (Spain) are assessed by means of the WRF-ARW/HERMES/CMAQ modeling system with high spatial-temporal resolution (1 km², 1 h). Seven emissions scenarios are defined taking into account the year 2004 vehicle fleet composition of the study areas and groups of vehicles susceptible of change under a realistic perspective. O₃ average concentration rises up to 1.3% in Barcelona and up to 2.5% in Madrid when introducing the emissions scenarios, due to the NO_x reduction in VOC-controlled areas. Nevertheless, NO₂, PM10 and SO₂ average concentrations decrease, up to 6.1%, 1.5% and 6.6% in Barcelona and up to 20.6%, 8.7% and 14.9% in Madrid, respectively. Concerning SO₂ and PM10 reductions the most effective single scenario is the introduction of 50% of NGV instead of the oldest commercial vehicles; it also reduces NO₂ concentrations in Barcelona, however in Madrid lower levels are attained when substituting 10% of the private cars. This work introduces the WRF-ARW/HERMES/CMAQ modeling system as a useful management tool and proves that the air quality improvement plans must be designed considering the local characteristics.     

Characterization of large fleets of vehicle exhaust emissions in middle Taiwan by remote sensing

Measurement of fleet emissions by means of remote sensing was conducted in middle Taiwan and the distributions and governing factors were characterized and examined. Results show the type of sampling sites is a dominant factor for the emission levels, and driving speeds and accelerations of the vehicles. In this study, the mean CO, HC, and NO concentrations at the urban and rural sites are apparently higher. The quantitative relationship between the pollutant concentration and mean speed or acceleration was established. Analysis of effect of the vehicle model year on the average fleet emissions was also conducted. It indicates those relatively older vehicles are higher emitters and contribute significantly more to total fleet emissions. On the other hand, the variation trends with model year are independent of the site characteristics and the effect of vehicle age on CO, HC, and NO emission is similar.     

A new method to compare vehicle emissions measured by remote sensing and laboratory testing: high-emitters and potential implications for emission inventories

A new method is presented which is designed to investigate whether laboratory test data used in the development of vehicle emission models adequately reflects emission distributions, and in particular the influence of high-emitting vehicles. The method includes the computation of a ‘high-emitter’ or ‘emission distribution’ correction factor for use in emission inventories. In order to make a valid comparison we control for a number of factors such as vehicle technology, measurement technique and driving conditions and use a variable called ‘Pollution Index’ (g/kg). Our investigation into one vehicle class has shown that laboratory and remote sensing data are substantially different for CO, HC and NO_x emissions, both in terms of their distributions as well as in their mean and 99-percentile values. Given that the remote sensing data has larger mean values for these pollutants, the analysis suggests that high-emitting vehicles may not be adequately captured in the laboratory test data.The paper presents two different methods for the computation of weighted correction factors for use in emission inventories based on laboratory test data: one using mean values for six ‘power bins’ and one using multivariate regression functions. The computed correction factors are substantial leading to an increase for laboratory-based emission factors with a factor of 1.7-1.9 for CO, 1.3-1.6 for HC and 1.4-1.7 for NO_x (actual value depending on the method). However, it also clear that there are points that require further examination before these correction factors should be applied. One important step will be to include a comparison with other types of validation studies such as tunnel studies and near-road air quality assessments to examine if these correction factors are confirmed. If so, we would recommend using the correction factors in emission inventories for motor vehicles.     

Emissions variation in urban areas resulting from the introduction of natural gas vehicles: Application to Barcelona and Madrid Greater Areas (Spain)

On-road traffic is the major contributor to pollutant emissions in urban areas. Nowadays different emission abatement strategies are being tested in order to improve urban air quality (e.g. the European Commission currently promotes the use of natural gas as an alternative fuel). Several feasible scenarios regarding the introduction of natural gas vehicles (NGV) are studied in the two main cities of Spain (Barcelona and Madrid) by using the HERMES emission model. The most suitable emission factors to NGV are selected among those available in the literature. The account of emissions in the base case scenario estimated for a typical summertime polluted day of the year 2004 reflects that in Barcelona 86% of primary pollutants come from on-road traffic compared to 93% in Madrid, because of the heavier industrial activity in the former. The introduction of NGV in urban zones would have a positive effect on emissions, whose extent largely depends on the substituted fleets and the conurbation characteristics. Maximum reductions in NO_x emissions in Madrid are attributed to the substitution of 10% of the oldest diesel and petrol cars, while in Barcelona the change of 50% of the oldest commercial light vehicles becomes more effective. PM_2.5 and SO₂ emissions can be significatively reduced with the introduction of NGV instead of the oldest commercial light vehicles. The substitution of conventional fuels by natural gas must reach around 4% to achieve significative reductions in traffic emissions (larger than 5%). This work focuses on air quality issues, therefore GHG emissions are not included, nevertheless this kind of associated impact has to be considered by the decision makers. Assessing the efficacy of environmental improvement strategies entails a realistic design of emission scenarios and their evaluation. The detailed emission account provides a fundamental basis for the air quality modelling and its comparison among scenarios.     

A bottom-up methodology to estimate vehicle emissions for the Beijing urban area

Vehicle exhaust emissions have posed a serious threat in recent years to the urban air quality of Beijing. It is necessary to accurately estimate the magnitude and distribution of these emissions in order to reduce the uncertainty of local scale air quality modeling assessment. This paper provides a bottom-up approach by combining vehicle emission factors and vehicle activity data from a travel demand model estimated at the grid level to generate vehicle emissions data for the Beijing urban area in 2005. In that year, vehicular emissions of HC, CO and NOx were respectively 13.33 × 10⁴, 100.02 × 10⁴ and 7.55 × 10⁴ tons. The grid-based emissions were also compared with the vehicular emission inventory developed by macro-scale approach. It shows this bottom-up approach can result in better estimates of the levels and spatial distribution of vehicle emissions than the macro-scale method that relies on more average and aggregated information.     

Methodology for spatio‐temporal predictions of traffic counts across an urban road network and generation of an on‐road greenhouse gas emission inventory

On‐road emission inventories in urban areas have typically been developed using traffic data derived from travel demand models. These approaches tend to underestimate emissions because they often only incorporate data on household travel, not including commercial vehicle movements, taxis, ride hailing services, and other trips typically underreported within travel surveys. In contrast, traffic counts embed all types of on‐road vehicles; however, they are only conducted at selected locations in an urban area. Traffic counts are typically spatially correlated, which enables the development of methods that can interpolate traffic data at selected monitoring stations across an urban road network and in turn develop emission estimates. This paper presents a new and universal methodology designed to use traffic count data for the prediction of periodic and annual volumes as well as greenhouse gas emissions at the level of each individual roadway and for multiple years across a large road network. The methodology relies on the data collected and the spatio‐temporal relationships between traffic counts at various stations; it recognizes patterns in the data and identifies locations with similar trends. Traffic volumes and emissions prediction can be made even on roads where no count data exist. Data from the City of Toronto traffic count program were used to validate the output of various algorithms, indicating robust model performance, even in areas with limited data.     

Is Compact Growth Good for Air Quality?

Problem: Explicitly prohibited from regulating the land use planning activities of municipal and county governments by the Clean Air Act (42 U.S.C. 131), the U.S. Environmental Protection Agency (EPA) has been forced to pursue an end-of-the-pipe approach to air quality management that has not proved successful in fully reducing ozone and fine particulate matter below health-based standards in many large U.S. cities. The persistence of these pollutants, in combination with a rapid rise in vehicle travel in recent decades, has raised concerns within the planning and public health communities about the long-term success of an air quality management program that is effectively divorced from the land use planning process.

Purpose: This work, which is part of an EPA-sponsored study titled Projecting the Impact of Land Use and Transportation on Future Air Quality (PLUTO), was intended to assess the effectiveness of compact growth in improving air quality at a geographic scale compatible with secondary pollution formation and transport and over a planning horizon sufficient to capture the longer-term benefits of regional land use change.

Methods: Future air quality is associated with alternative land development scenarios in this study through the integration of three separate and previously unrelated modeling components. These components consist of a set of standard population projection techniques, a household vehicle travel activity framework, and a mobile source emissions model (MOBILE 6) developed by the EPA.

Results and conclusions: The results of our analysis find the median elasticity of vehicle travel with respect to density change over time to be ?0.35, suggesting metropolitan areas can expect a 10% increase in population density to be associated with a 3.5% reduction in household vehicle travel and emissions. In addition, vehicle elasticities derived for urban and suburban census tracts across the 11 metro regions suggest density increments within urban zones (?0.43) to be more than twice as effective in reducing vehicle travel and emissions as density increments within suburban zones (?0.19).

Takeaway for practice: We found compactness to be associated with greater reductions in vehicle travel than in previous studies, which suggests land use change can play a measurable role in improving regional air quality over time. Importantly, we found where compact growth occurs to be critically important to determining the extent to which higher density development reduces vehicle travel and emissions. We found the densifi-cation of urban zones to be more than twice as effective in reducing vehicle miles of travel and emissions as the densification of suburban zones, suggesting compact growth to be better for air quality than historical patterns of growth when densifying urban zones is given priority over non-urban zones.     

On-road vehicle emission inventory and its uncertainty analysis for Shanghai, China

As vehicle population and activity increase, vehicle emissions are becoming the most predominant source of air pollution in Shanghai, China. It has become important to accurately estimate the traffic emissions in this city. This paper presents a bottom-up approach based on the International Vehicle Emission (IVE) model to develop the vehicle emission inventory for Shanghai. The results show that the total emissions of CO, VOC, NO(X) and PM from vehicles in Shanghai in 2004 were 57.06 x 10(4) t, 7.75 x 10(4) t, 9.20 x 10(4) t and 0.26 x 10(4) t, respectively. About 20% of the total emissions were emitted during the cold start period. Heavy-duty vehicles such as trucks and buses contributed over half of NO(X) and PM. Motorcycles and mopeds provided 45.0% of VOC and 36.3% of PM. Light-duty vehicles are the main source of CO emissions. An assessment of vehicle emissions by time of day and road type was also discussed. The three peak emission periods accounted for 54% to 56% of the total emissions during the day and more than 50% of the total emissions were emitted on the arterial roads. Finally, the study focused on the uncertainty analysis of two critical factors: emission factors and the estimate of the total Vehicle Kilometers Traveled (VKT). The analysis indicates that the emission factors calculated in this paper are close to those factors measured during on-road testing, and the difference between the VKT used in this paper and other calculations is less than 10%.     

Estimating the contributions of mobile sources of PAH to urban air using real-time PAH monitoring.

Motor vehicles are a significant source of airborne polycyclic aromatic hydrocarbons (PAH) in many urban areas. Traditional approaches used in determining the relative contributions of individual vehicle types to the total amount of PAH in air have been based on the analysis of integrated samples of airborne particles and gases for the presence of chemical tracers indicative of the vehicles from which the chemicals derived. As an alternative, we have used a photoelectric aerosol sensor (PAS) capable of measuring PAH levels in real-time in the emissions plumes from motor vehicles. We placed the PAS near a traffic-light in Kenmore Square, a busy crossroads in downtown Boston (MA, USA). A video camera co-located at the site recorded the vehicles passing the sensor, and this record was correlated with the PAS data. During a 5-day monitoring period (approximately 59 h) in the summer of 1998, over 34,000 motor vehicles were counted and classified and over 24,000 PAS readings were recorded (frequency = 1/8.6 s). The composition of the vehicle population was 94% passenger vehicles, 1.4% buses, 2.6% small trucks, 1.3% medium trucks, 0.35% large trucks, and 0.45% garbage and construction trucks. In analyzing the PAS data, it was assumed that the highest PAS measurements--those that exceeded the 95% critical level of the 5-min moving average of all the PAS measurements--were indicative of primary vehicular emissions. We found that approximately 46% of the mass of particle-bound PAH (i.e. approximately 46% of the integrated area under the PAS signal vs. time plots) was attributable to primary emissions from motor vehicles passing the sensor. Of this, 35-61% was attributable to passenger vehicles (cars, pickup trucks, and sports utility vehicles) and 39-65% was attributable to non-passenger vehicles [buses (14-23%), small trucks (12-20%), medium trucks (8.4-14%), large trucks (2.9-4.8%) and garbage and construction trucks (1.9-3.2%)]. Our results suggest that on a per vehicle basis, buses and trucks--the majority of which run on diesel fuel--emitted greater amounts of particle-bound PAH than passenger vehicles. Overall, we found that real-time photoelectric aerosol sensing (in combination with video photography) is useful for estimating the contributions of airborne PAB from different vehicle types. Due to the physical constraints of our monitoring site and the high volumes of traffic, however, it was not possible to uniquely attribute PAS signals to individual vehicles.     

Estimation of automobile emissions and control strategies in India

Rapid, but unplanned urban development and the consequent urban sprawl coupled with economic growth have aggravated auto dependency in India over the last two decades. This has resulted in congestion and pollution in cities. The central and state governments have taken many ameliorative measures to reduce vehicular emissions. However, evolution of scientific methods for emission inventory is crucial. Therefore, an attempt has been made to estimate the emissions (running and start) from on-road vehicles in Chennai using IVE model in this paper. GPS was used to collect driving patterns.The estimated emissions from motor vehicles in Chennai in 2005 were 431, 119, 46, 7, 4575, 29, and 0.41 tons/days respectively for CO, VOC, NO_x, PM, CO_2, CH₄ and N₂O. It is observed from the results that air quality in Chennai has degraded. The estimation revealed that two and three-wheelers emitted about 64% of the total CO emissions and heavy-duty vehicles accounted for more than 60% and 36% of the NO_x and PM emissions respectively. About 19% of total emissions were that of start emissions. It is also estimated that on-road transport contributes about 6637 tons/day CO₂ equivalent in Chennai. This paper has further examined various mitigation options to reduce vehicular emissions. The study has concluded that advanced vehicular technology and augmentation of public transit would have significant impact on reducing vehicular emissions.     

基于高分辨率遥感影像的车辆信息提取方法研究

从高分辨率遥感影像上进行车辆信息提取可以作为地面车辆分布信息监测的一种全新的方式。文章采用Adaboost算法和多尺度影像分割,结合城市地区地籍资料等现有的资料,分别对大飞机DMC航摄影像和Quickbird-2卫星影像进行了车辆信息提取试验,总结出可以有效地从高分辨率遥感影像上提取车辆对象的方法流程,并对提取正确率等试验结果进行了分析。     

Real‐Time Estimation of Pollution Emissions and Dispersion from Highway Traffic

Traffic‐related air pollution is a serious problem with significant health impacts in both urban and suburban environments. Despite an increased realization of the negative impacts of air pollution, assessing individuals' exposure to traffic‐related air pollution remains a challenge. Obtaining high‐resolution estimates are difficult due to the spatial and temporal variability of emissions, the dependence on local atmospheric conditions, and the lack of monitoring infrastructure. This presents a significant hurdle to identifying pollution concentration hot spots and understanding the emission sources responsible for these hot spots, which in turn makes it difficult to reduce the uncertainty of health risk estimates for communities and to develop policies that mitigate these risks. We present a novel air pollution estimation method that models the highway traffic state, highway traffic‐induced air pollution emissions, and pollution dispersion, and describe a prototype implementation for the San Francisco Bay Area. Our model is based on the availability of real‐time traffic estimates on highways, which we obtain using a traffic dynamics model and an estimation algorithm that augments real‐time data from both fixed sensors and probe vehicles. These traffic estimates combined with local weather conditions are used as inputs to an emission model that estimates pollutant levels for multiple gases and particulates in real‐time. Finally, a dispersion model is used to assess the spread of these pollutants away from the highway source. Maps generated using the output of the dispersion model allow users to easily analyze the evolution of individual pollutants over time, and provides transportation engineers and public health officials with valuable information that can be used to minimize health risks.     

Trends in hydrocarbon fleet emissions at four UK highway sites.

The on-road hydrocarbon emissions of vehicles at four sites in the UK have been monitored using remote sensing equipment. The single lane highway sites in London (Haringey and Southwark), Middlesborough and Leicester were monitored between May 1994 and October 1995. Analysis of the results shows that there is both a large majority of low emitting vehicles which contribute little to fleet hydrocarbon emissions and a small minority of high emitting vehicles which contribute significant proportions to fleet hydrocarbon emissions at all sites. This also results in a skewing of the data set so that a pattern of high mean values and lower median values is consistently observed. Analysis of model year data suggests a low association between vehicle age and mean hydrocarbon emissions for vehicles produced prior to 1983 but the relationship improves after 1983 with regression analyses giving r2 values as high as 0.96. Relatively new high polluting vehicles are the greatest contributors to fleet emissions with, on average, 52% of hydrocarbon fleet emissions being produced by these vehicles from model years 1985-1991. Therefore, fleet emissions could be significantly reduced if new highly polluting vehicles were subject to regular emissions testing followed by appropriate remedial action or were removed from the highway by the withdrawal of their vehicle registration. Older vehicles play a minor role in fleet emissions with, on average, only 13% of hydrocarbon fleet emissions being produced by vehicles registered prior to 1983.     

Modelling instantaneous traffic emission and the influence of traffic speed limits

This paper considers the effect of active speed management on traffic-induced emissions. In particular, the traffic emissions caused by acceleration and deceleration of vehicles are modelled based on an instantaneous emission model integrated with a microscopic traffic simulation model. The emission model is based on empirical measurements which relate vehicle emission to the type, the instantaneous speed and acceleration of the vehicle. The traffic model captures the second-by-second speed and acceleration of individual vehicles travelling in a road network based on their individual driving style, the vehicle mechanics, and their interaction with other traffic and with traffic control in the network. The integrated model is applied to test a new technology to actively manage the driving speed of the vehicles in an urban network. Their impacts on vehicle emission in the network are assessed to give an indication of the relative effectiveness of the different technological designs and different levels of driver responses. The results show that, while the speed management has effectively reduced the average speed of the traffic, their impact on vehicle emissions is complex. For the study network, the frequent acceleration and deceleration movements in the network has significantly reduced the effect of the reduced average speed on emission. The net results are that the active speed management has no significant impact on pollutant emissions. The study suggests that the analysis of the environmental impacts of any traffic management and control policies is a complex issue and requires detailed analysis of not only their impact on average speeds but also on other aspects of vehicle operation such as acceleration and deceleration.     

机动车颗粒物排放控制策略研究

颗粒物已经成为造成环境污染和影响人体健康的主要污染物之一,而机动车颗粒物排放占污染物的60%以上。目前中国对机动车颗粒物排放的研究较少,没有系统提出相应的控制策略。文章首先分析了机动车颗粒物的生成机理及影响因素;根据《中国机动车污染防治年报》统计数据,使用MATLAB建立了汽车、低速汽车及机动车数量与颗粒物排放量之间的数学模型,预测未来5 a内的机动车颗粒物的排放总量。结果表明机动车颗粒物排放逐年增加,2015年将达到1.032 2×10 6 t;而低速汽车数的PM排放量会逐年缓慢降低,这主要受国家政策影响。最后,根据分析预测结果,提出了机动车颗粒物排放控制策略。     

Local Air Pollution Control in the USA: Potential Lessons for the Introduction of Air Quality Management Areas and Action Plans in the UK

During the 1990s air quality re-emerged as an important environmental policy issue in the UK. Particular concern is now being focused on vehicle emissions, which are creating significant health problems for vulnerable populations in urban areas. National air quality standards have now been established and where these are not being met, under section 82 of the Environment Act 1995, local authorities are obliged to designate Air Quality Management Areas and institute appropriate remedial measures. This approach echoes that taken in the USA since the 1970s, where non-compliant areas have been designated as non-attainment areas, and state and local governments have prepared state implementation plans and attainment plans in response. This paper provides an overview of the institutional arrangements for the control of air pollution at the local level in the USA and considers the extent to which these provide possible lessons for the new arrangements in the UK.     

Study on the influence of meteorological conditions and the street side buildings on the pollutant dispersion in the street canyon

As cities grow, automobile exhaust pollution is worsening, which has become a major problem of air pollution, even it is a serious threat to the physical and mental health of residents. Thus, to study its diffusion law and influential factors occupies a count for much position. The paper analyzes the factors that affect the dispersion of urban vehicle emissions in street canyon to evaluate the research method of pollutant dispersion. In addition, the influences of different wind speeds and wind directions, the roof shape of buildings on both street sides, and the relative height of the two sides of buildings on the street canyon, on airflow field and pollutant dispersion are simulated. It is shown that the wind speed, the wind direction and the buildings on both sides have a great impact on the airflow and contaminant dispersion in the street canyon. The results provide scientific basis for controlling, monitoring and evaluating the urban motor vehicle emissions, besides the reasonable layout and the programme of urban streets.     

Integrated air quality modelling for a designated air quality management area in Glasgow

Currently, most local authorities in the UK use well-established Gaussian-type dispersion models to predict the air quality in urban areas. The use of computational fluid dynamics (CFD) in integrated urban air quality modelling is still in its infancy, despite having an enormous potential in assessing and improving natural ventilation in built-up areas. This study assesses the suitability of a general CFD code (PHOENICS) for use in integrated urban air quality modelling for regulatory purposes. An urban air quality model of a designated air quality management area in the city centre of Glasgow has been developed by integrating traffic flow data for urban road networks, traffic pollutant emission data and a three-dimensional CFD dispersion model of a complex configuration of street canyons.

The results are in good agreement with field measurements taken during the continuous monitoring campaign, and show that a general CFD code has indeed the potential for regulatory use. Although this numerical tool has demonstrated satisfactory performance, it is observed that small differences in monitoring station positioning may yield significant variations of the measured mean concentration, due to large values of horizontal and vertical local concentration gradients. Although, at this stage, the accuracy of the developed Glasgow urban air quality model is highly dependent on the experience of its users, it is believed that use of a CFD code (such as PHOENICS) could benefit urban planners, architects, HVAC engineers and all other professionals interested in public health.     

Actual car fleet emissions estimated from urban air quality measurements and street pollution models.

A method to determine emissions from the actual car fleet under realistic driving conditions has been developed. The method is based on air quality measurements, traffic counts and inverse application of street air quality models. Many pollutants are of importance for assessing the adverse impact of the air pollution, e.g. NO2, CO, lead, VOCs and particulate matter. Aromatic VOCs are of special great concern due to their adverse health effects. Measurements of benzene, toluene and xylenes were carried out in central Copenhagen since 1994. Significant correlation was observed between VOCs and CO concentrations, indicating that the petrol engine vehicles are the major sources of VOC air pollution in central Copenhagen. Hourly mean concentrations of benezene were observed to reach values of up to 20 ppb, what is critically high according to the WHOs recommendations. Based on inverse model calculation of dispersion of pollutants in street canyons, an average emission factor of benzene for the fleet of petrol fuelled vehicles was estimated to be 0.38 g/km in 1994 and 0.11 in 1997. This decrease was caused by the reduction of benzene content in Danish petrol since summer 1995 and increasing percentage of cars equipped with three-way catalysts. The emission factors for benzene for diesel-fuelled vehicles were low.