Modelling of vehicular exhausts – a review

A review of the air pollution studies carried out to study the dispersion of vehicular exhaust emissions (VEEs) has been made. The review includes the modelling studies in the domain, primarily, of analytical modelling – deterministic mathematical models and numerical models, and statistical models. Various model performance evaluation and comparative assessment studies have also been discussed. Further, the studies conducted to model VEEs at the urban road intersection and urban street canyons have also been reviewed.     

Experimental study of the impact of structural geometry and wind direction on vehicle emissions in urban environment

Vehicle emissions inside an urban environment are investigated using a wind-tunnel under neutral atmospheric conditions. The urban environment was formed as street canyon model. The diffusion flow field in the boundary layer inside the street canyon was examined at different locations of varying geometry of the street and wind directions in the downwind distance of the leeward side of the street canyon model. The results show that the vertical velocity increases as the aspect ratio increases and with wind direction increases from θ = 90°. The pollutant concentration increases as the aspect ratio decreases. The pollutant concentration decreases as the wind direction increases from θ = 90°. The pollutant concentration distributions indicate that the variability of the structure, geometry and wind direction inside the street canyon are important parameters for estimating air quality in the urban street canyon.     

Traffic pollution inventories and modeling in metropolitan Dhaka,Bangladesh

Several monitoring and surveys on ambient concentration of oxides of nitrogen (NO_x), lead (Pb), particulate matter (PM), carbon monoxide (CO) and black smoke have been carried out by the author, Bangladesh Atomic Energy Commission (BAEC), Department of Civil Engineering, Bangladesh University of Engineering and Technology (BUET), and Department of Environment (DOE), Bangladesh Government at different street intersections of metropolitan Dhaka. In addition, all traffic pollutant concentrations at 82 street intersections were estimated using the Gaussian Plume Model. The surveys and the analysis were undertaken primarily to provide an independent check on the pollutant concentration and to determine if there is any violation of the international compliance. The study covers, for the first time in its type, wide areas of road intersections and surveyed concentration of oxides of nitrogen. It has been observed that the concentration of NO_x, black smoke, lead, and PM violate both the national and international standards in metropolitan Dhaka. In addition, the concentration of CO is found relatively higher during the noon buildups.     

Estimation of road transport related air pollution in Saint Petersburg using European and Russian calculation models

The paper analyzes Russian and European emission and dispersion models aimed at the estimation of road transport related air pollution on street and regional scale as exemplified with St. Petersburg, Russia. It demonstrates the results of model calculations of peak concentrations of main harmful substances (NО_X, CO and PM₁₀) along the St. Petersburg Ring Road at high traffic volume and adverse meteorological conditions (calm, temperature inversion) executed by means of a Russian street pollution model, and it evaluates the computed results against the measurements from monitoring stations. The paper also examines the ways of adaptation of the COPERT IV model – a software tool for calculation of air pollutant and greenhouse gas emissions from road transport on regional or country scale – to the inventory conditions of the Russian Federation, compares the COPERT IV numerical estimates with the national inventory data. It also reveals the obstacles and possibilities in the harmonization of the Russian and European approaches.     

Simulations of pollutant dispersion at toll plazas using three-dimensional CFD models

Toll plazas are particularly susceptible to build-ups of vehicle-emitted pollutants because vehicles pass through in low gear. To look at this, three-dimensional computational fluid dynamics simulations of pollutant dispersion are used on the standard k − ε turbulence model. The effects of wind speed, wind direction and topography on pollutant dispersion were discussed. The Wuzhuang toll plaza on the Hefei-Nanjing expressway is considered, and the effects of the retaining walls along both sides of the plaza on pollutant dispersion is analysed. There are greater pollutant concentrations near the tollbooths as the angle between the direction of the wind and traffic increases implying that retaining walls impede dispersion. The slope of the walls has little influence on the variations in pollutant concentration.     

Influence of coordinated traffic lights parameters on roadside pollutant concentrations

The paper examines the effects of coordinated traffic lights on CO and C₆H₆ roadside concentrations in an urban area of Palermo in Southern Italy. Traffic loop detectors and one pollution-monitoring are used to collect data for use in DRACULA traffic microsimulator software. CO and C₆H₆ roadside concentrations associated with varying cycle and offset times of the coordinated traffic lights are estimated using a neural network. Two functions were set up describing the relations of pollutant concentrations in term of cycle and offset time.     

Urban roadside monitoring and prediction of CO,NO2 and SO2 dispersion from on-road vehicles in megacity Delhi

The study inspects the traffic-induced gaseous emission dispersion characteristics from the urban roadside sites in Delhi, India. The concentration of pollutants viz. CO, NO₂ and SO₂ along with traffic and ambient atmospheric conditions at five selected local urban road sites were simultaneously measured. A developed General Finite Line Source Model (GFLSM) was used to predict the local roadside CO, NO₂ and SO₂ concentrations. A comparison of the observed and predicted values emission parameters using GFLS model has shown that the predicted values for SO₂, CO and NO₂ at all the selected local urban roadside locations are found to lie within the error bands of 5%, 6%, and 7% respectively. A high level of agreement was found between the monitored and estimated CO, NO₂ and SO₂ concentration data. From the study, it has also been established that the developed model exhibits the capability of reasonably predicting the characteristics of gaseous pollutants dispersion from on-road vehicles for the urban city air quality.     

Atmospheric dispersion modeling near a roadway under calm meteorological conditions

Atmospheric pollutant dispersion near sources is typically simulated by Gaussian models because of their efficient compromise between reasonable accuracy and manageable computational time. However, the standard Gaussian dispersion formula applies downwind of a source under advective conditions with a well-defined wind direction and cannot calculate air pollutant concentrations under calm conditions with fluctuating wind direction and/or upwind of the emission source. Attempts have been made to address atmospheric dispersion under such conditions. This work evaluates the performance of standard and modified Gaussian plume models using measurements of NO₂, PM₁₀, PM_2.5, five inorganic ions and seven metals conducted near a freeway in Grenoble, France, during 11–27 September 2011. The formulation for calm conditions significantly improves model performance. However, it appears that atmospheric dispersion due to vehicle-induced turbulence is still underestimated. Furthermore, model performance is poor for particulate species unless road dust resuspension by traffic is explicitly taken into account.     

Allocation of onroad mobile emissions to road segments for air toxics modeling in an urban area

Dispersion models are useful tools for setting emission control priorities and developing strategies for reducing air toxics emissions. Previous methodologies for modeling hazardous air pollutant emissions for onroad mobile sources are based on using spatial surrogates to allocate county level emissions to grid cells. A disadvantage of this process is that it spreads onroad emissions throughout a grid cell instead of along actual road locations. High local concentrations may be underestimated near major roadways, which are often clustered in urban centers. Here, we describe a methodology which utilizes a Geographic Information System to allocate benzene emissions to major road segments in an urban area and model the segments as elongated area sources. The Industrial Source Complex Short Term dispersion model is run using both gridded and link-based emissions to evaluate the effect of improved spatial allocation of emissions on ambient modeled benzene concentrations. Allocating onroad mobile emissions to road segments improves the agreement between modeled concentrations when compared with monitor observations, and also results in higher estimated concentrations in the urban center.     

Distinguishing the land use effects of road pricing based on the urban form attributes

This paper studies the effects of road pricing on land use under different development scenarios (business as usual scenario and transit oriented development scenario) by a quantitative method, which combines the integrated land use and transport interaction model (TRANUS model) with the scenario-planning techniques. Moreover, in order to further analyze the differences of the land use effects of road pricing on traffic analysis zones (TAZs) with different urban form attributes, a quantitative classification method combining factor analysis and cluster analysis is then used to quantitatively classify TAZs. The results demonstrate that the effects of road pricing on the land use of a specific region depend on the urban form attributes of the region. The higher the densities of employments and population, and better street design (high densities of street and intersections) and public transportation condition, the less the region is negatively affected by road pricing, and vice versa. More importantly, rail transit can alleviate the negative impact of road pricing on commercial development and population concentration of the region. Therefore, before introducing a road pricing policy, it is necessary to develop public transport system, especially rail transit.     

Estimating near-road pollutant dispersion: A model inter-comparison

A model inter-comparison study to assess the abilities of steady-state Gaussian dispersion models to capture near-road pollutant dispersion has been carried out with four models (AERMOD, run with both the area-source and volume-source options to represent roadways, CALINE, versions 3 and 4, ADMS and RLINE). Two field tracer studies are used: the Idaho Falls tracer study and the Caltrans Highway 99 tracer study. Model performance measures are calculated using concentrations (observed and estimated) that are paired in time and space, since many of the health related questions involve outcomes associated with spatially and temporally distributed human activities. All four models showed an ability to estimate the majority of downwind concentrations within a factor of two of the observations. RLINE, AERMOD-V, and ADMS, also have the capability to predict concentrations upwind of the roadway that result from low-speed meandering of the plume. Generally, RLINE, ADMS, and AERMOD (both source types) had overall performance statistics that were broadly similar, while CALINE 3 and 4 both produced a larger degree of scatter in their concentration estimates. The models performed best for near-neutral conditions in both tracer studies, but had mixed results under convective and stable conditions.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach

This paper applies artificial neural network to predict hourly air pollutant concentrations near an arterial in Guangzhou, China. Factors that influence pollutant concentrations are classified into four categories: traffic-related, background concentration, meteorological and geographical. The hourly averages of these influential factors and concentrations of carbon monoxide, nitrogen dioxide, particular matter and ozone were measured at three selected sites near the arterial using vehicular automatic monitoring equipments. Models based on back-propagation neural network were trained, validated and tested using the collected data. It is demonstrated that the models are able to produce accurate prediction of hourly concentrations of the pollutants respectively more than 10 h in advance. A comparison study shows that the neural network models outperform multiple linear regression models and the California line source dispersion model.     

Real-time prediction of extreme ambient carbon monoxide concentrations due to vehicular exhaust emissions using univariate linear stochastic models

Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box–Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India.     

Cycleways and footpaths: What separation is needed for equivalent air pollution dose between travel modes?

Cycling and walking are being promoted in many urban areas as alternatives to motorised transport for health, environmental, and financial reasons. The reduced congestion and resulting decrease in the overall amount of pollution reduced can be expected to result in health benefits for the community. However, active commuters, due to their increased respiration rates and often increased travel times can expect to receive larger doses of air pollution compared with those using motorised forms of transport. However, given the large dropoff in concentrations away from a road, it can be expected that significant reductions can be achieved even with relatively small increases in separation between the path of cyclists/pedestrians and motor vehicles.This study presents a simple methodology for calculating the separation needed for cyclists and pedestrians to experience the same air pollution dose as car commuters. An example is given based on carbon monoxide (CO) data collected in a field campaign consisting of a car driver, a cyclist and a pedestrian travelling on a 2600 metre loop of road in Auckland. For this case study, the estimated distance from the centreline needed for cyclists and pedestrians to receive an equivalent dose of CO as motorists was found to range from 5.8 to 14.2 m depending on the commuting mode and the dispersion state of the atmosphere at the site. This was equal to a CO concentration reduction of 0.1–0.14 ppm per metre. Recommendations on facility modifications and route selections have been made to make active mode commuting safer.     

A hybrid model predictive control for traffic flow stabilization and pollution reduction of freeways

In this work a control system is developed and analyzed for the suppression of moving jamwaves and the reduction of pollutant concentrations near motorways. The system is based on the second-order macroscopic freeway traffic model METANET, joined by an emission dispersion model, introduced in a previous work of the authors. For the control tasks dedicated controllers are designed, both using the nonlinear model predictive control method. The control objectives require a distinction in the utilized control measures, thus different controllers are designed and used in predefined control modes. The first mode of the controller is responsible for keeping pollutant concentrations below prescribed limits under stable conditions. The second mode of the controller is working in case of a shockwave threat, aiming for traffic stabilization. Between the control modes switching is based on an appropriate rule set that satisfies the stability of the controlled system. The hybrid controller structure is realized by a finite automata. A complex case study is presented for the evaluation of the suggested controller.     

Computer simulation of impacts of a chlorine tanker truck accident

The aim of the study was to present the author’s original modelling programs of pollution dispersion in an urban environment. The programs outlined herein are based on a diagnostic model of air velocity field and Langrangian particle model. In both modelling programs author’s elements of mathematical modelling were applied. The models have been validated and verified. Geographic Information System (GIS) Idrisi Andes was applied in the pre-processing stage.The development of author’s original computer program and stages of hazardous material propagation modelling were discussed.The results of computations and analysis of pollution dispersion caused by a chlorine tanker truck collision and chlorine release into atmosphere were presented. It was simulated that the accident took place in the city of Bielsko-Biała, on a bypass in a built-up area causing leakage of 10 t of chlorine. The computer simulations conducted for two wind direction scenarios allow to conclude that the total area affected by the pollutant cloud with concentrations above threshold levels could be over 2 km², with 5000 lethally exposed people.     

The efficacy of low emission zones in central London as a means of reducing nitrogen dioxide concentrations

This paper considers the effects of different strategies that might be considered to reduce the impact made by road traffic on air pollution in London. The management of road traffic in large urban areas is one of many options being considered to reduce pollutant emissions to meet statutory air pollution objectives. Increasingly, the concept of a low emission zone (LEZ) is being proposed as a means of achieving this reduction. An assessment has been made of different LEZ scenarios in central London, which involve reducing traffic flow or modifying the vehicle technology mix. Methods of predicting annual mean nitrogen dioxide concentrations utilising comprehensive traffic data and air pollution measurements have been used to develop empirical prediction models. Comparisons with statutory air pollution objectives show that significant action will be required to appreciably decrease concentrations of nitrogen dioxide close to roads. The non-linear atmospheric chemistry leading to the formation of nitrogen dioxide, results in a complex relationship between vehicle emissions and ambient concentrations of the pollutant. We show that even ambitious LEZ scenarios in central London produce concentrations of nitrogen oxides that are achieved through a “do nothing” scenario only five years later.     

基于LEAP模型的城市客运交通能耗和污染物排放预测

我国交通运输业能源消耗量与污染物排放量日益增多,交通部门的节能减排措施研究迫在眉睫。本论文基于LEAP模型构建了某城市客运交通能耗与污染物排放模型,并预测了基准情景、政策情景、技术情景及综合情景下该城市客运交通2014-2030年之间的能耗及污染物排放情况。研究表明,三种发展情景下该城市能源需求量及污染物排放较基准情景均有减少,其中综合情景效果最佳,综合情景在2030年的能源消耗与CO2排放可分别减少56.98%和54.55%,CO、HC、NOx与PM2.5可分别减排67.39%、67.27%、51.43%与75.38%。因此应大力发展公共交通,尤其是轨道交通,同时限制私家车的无节制发展,并推广节能环保技术以改善终端利用层次能源结构。