Driving speeds in Europe for pollutant emissions estimation

The sensitivity of the pollutant emissions as regards the driving speed is demonstrated using emission functions currently available from the literature. An accurate and detailed knowledge of the actual driving speeds is then fundamental for emissions estimations and inventories. However, speed information is often limited and heterogeneous. Through a European synthesis, we examine the various means of investigations: surveys, vehicle instrumentation, traffic modelling, etc.The available statistics provide a high number of reference values for passenger cars and duty vehicles by broad categories and highlight the influence of numerous factors on speed: time period, city size and area, trips origin and destination and vehicle types. Speed estimations and ranges are proposed for the driving in urban areas, on rural roads and on motorways.The significant variations of the speed according to the time of the day, to the areas of a city, and the large dispersion for a given situation raise the question of using single average values. In fact, emissions estimation can be affected by 30% by the quality of the driving speed data.     

An assessment of pollutant emissions due to air traffic at Nikola Tesla International Airport,Belgrade, and the link between local air quality and weather types

The assessment of local air pollution due to air traffic is an important issue from the standpoint of human health. An advanced approach using a landing and take-off cycle method is employed to assess emissions of nitrogen oxides (NO_x), carbon monoxide (CO), hydrocarbon (HC), and sulphur oxides (SO_x). Emissions of both volatile and non-volatile particulate matter are estimated using the new First-Order Approximation methodology. As synoptic situations (weather) determine the transport of pollutants in the air as well as their scavenging, the weather type for each day is classified for the study period (2008–2015).Due to a significant increase in air traffic at Nikola Tesla International Airport, Belgrade, in the last eight years, emissions of all considered pollutants have also increased. Emissions of NO_x and CO were the highest (totals for eight years were 2976.03 and 2875.66 tons, respectively). An analysis of weather types showed that the most frequent were warm, dry, anticyclones (AWD) and cyclones (low-pressure systems) including the passage of a cold front (CCF). The frequency of occurrence of AWDs and CCFs was 28.3% and 21.6%, respectively. An AWD is very unfavourable from the viewpoint of local air pollution, especially during the cold part of year, due to a shallow temperature inversion and fog formation in the morning confining the pollutants to the emission location for a longer time span. CCFs are also adverse due to the prevailing westerly and north-westerly winds that transport pollutants toward the city.     

Instantaneous emissions models set in GIS for the TRANSIMS outputs

A novel methodology that provides more detailed estimates of vehicular polluting emissions is offered, in order to contribute to the improvement and the precision of emission inventories of vehicle sources through the consideration of instantaneous speed changes or acceleration instead of average vehicular speeds. This paper presents the construction and application of an instantaneous emissions model designated hereunder as “Transims’s Snapshots-Based Emissions”, which is set on a Geographic Information System that incorporates instantaneous fuel consumption factors and fuel-based emission factors to attain highest resolution of both, spatial and temporal distribution of vehicular polluting emissions based on traffic simulation through cellular automata with TRANSIMS. This work was applied to the road network of the Mexico City Metropolitan Area as case study. The development of this powerful tool led to obtaining 86,400 maps of the spatial and temporal distribution of vehicular emissions per vehicle circulating on the road network, including the following pollutants: carbon monoxide and carbon dioxide, nitrogen oxides, total hydrocarbons, sulfur oxides, polycyclic aromatic hydrocarbons, black carbon, particles PM₁₀ and PM_2.5. The said maps allowed identification with highest level of detail, of the emissions and Hot-spots of fuel consumption. Also, the model permitted to obtain the emissions’ longitudinal profiles of a given vehicle along its route. This study shows that the integration method of the polynomial regression models represents an opportunity for each city to develop more easily and openly its own regional emissions models without requiring deeper programming knowledge.     

The costs and benefits of reducing SO2 emissions from ships in the US West Coastal waters

Potential costs and benefits of policy options for reducing offshore ship pollution are examined using a meta-analysis of studies synthesized regionally for the US West Coast. Net benefits of reducing SO₂ emissions from cargo ships in the US West Coast waters are found to range between $98 million and $284 million, annually; the benefit–cost ratio varies between 1.8 and 3.36, depending on the size of the control area and the sulfur content limit. The results show that about 21,000 tons of on-land equivalent SO₂ emissions or about 33% of SO₂ emissions from all mobile sources in California in 2005 can be reduced annually if the US West Coast exclusive economic zone is designated as an International Maritime Organization-compliant SO_x emission control area (SECA) with fuel-sulfur content not exceeding 1.5%. The analysis demonstrates that designating this area reduces more emissions than establishing a smaller zone at a lower but favorable benefit-cost ratio. Control measures that require 0.5% low-sulfur fuels reduce more SO₂ emissions, and also may have higher net benefits. Technological alternatives may achieve benefits of emissions reductions on the US West Coast across higher ranges of potential fuel prices. Combinations of fuel switching and control technology strategies provide the most cost-effective benefits from SECAs on the US West Coast and other world regions.     

Simulating the air quality impacts of traffic calming schemes in a dense urban neighborhood

In this study, the effects of isolated traffic calming measures and area-wide calming schemes on air quality in a dense neighborhood were estimated using a combination of microscopic traffic simulation, emission, and dispersion modeling. Results indicated that traffic calming measures did not have as large an effect on nitrogen dioxide (NO₂) concentrations as the effect observed on nitrogen oxide (NO_x) emissions. Changes in emissions resulted in highly disproportional changes in pollutant levels due to daily meteorological conditions, road geometry and orientation with respect to the wind. Average NO₂ levels increased between 0.1% and 10% with respect to the base-case while changes in NO_x emissions varied between 5% and 160%. Moreover, higher wind speeds decreased NO₂ concentrations on both sides of the roadway. Among the traffic calming measures, speed bumps produced the highest increases in NO₂ levels.     

Development of an emissions inventory model for mobile sources

Traffic represents one of the largest sources of primary air pollutants in urban areas. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentrations of a wide range of pollutants. A mutual characteristic of most of these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emissions inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for a wide range of vehicle types. The majority of inventories are compiled using ‘passive’ data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. Current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this paper, a methodology for estimating emissions from mobile sources using real-time data is described. This methodology is used to calculate emissions of sulphur dioxide (SO₂), oxides of nitrogen (NO_x), carbon monoxide (CO), volatile organic compounds (VOC), particulate matter less than 10 μm aerodynamic diameter (PM₁₀), 1,3-butadiene (C₄H₆) and benzene (C₆H₆) at a test junction in Dublin. Traffic data, which are required on a street-by-street basis, is obtained from induction loops and closed circuit televisions (CCTV) as well as statistical data. The observed traffic data are compared to simulated data from a travel demand model. As a test case, an emissions inventory is compiled for a heavily trafficked signalized junction in an urban environment using the measured data. In order that the model may be validated, the predicted emissions are employed in a dispersion model along with local meteorological conditions and site geometry. The resultant pollutant concentrations are compared to average ambient kerbside conditions measured simultaneously with on-line air quality monitoring equipment.     

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.     

Anticipating emission-sensitive traffic management strategies for dynamic delivery routing

Traffic pollution is an increasing challenge for cities. Emissions such as nitrogen dioxides pose a major health threat to the city’s inhabitants. These emissions often accumulate to critical levels in local areas of the city. To react to these critical emission levels, cities start implementing dynamic traffic management systems (TMS). These systems dynamically redirect traffic flows away from critical areas. These measures impact the travel speeds within the city. This is of particular importance for parcel delivery companies. These companies deliver goods to customers in the city. To avoid long delivery times and higher costs, companies already adapt their routing with respect to changing traffic conditions. Still, a communication with the TMS may allow anticipatory planning to avoid potentially critical areas in the city. In this paper, we show how communication between TMS and delivery companies results in benefits for both parties. To exploit the provided information, we develop a dynamic routing policy anticipating potential future measures of the TMS. We analyze our algorithm in a comprehensive case study for the TMS of the city of Braunschweig, Germany, a city often used as reference for a typical European city layout. We show that for the delivery company, integrating the TMS’ information in their routing algorithms reduces the driving times significantly. For the TMS, providing the information results in less traffic in the polluted areas.     

Simulating the environmental effects of isolated and area-wide traffic calming schemes using traffic simulation and microscopic emission modeling

This study focuses on the development of a microscopic traffic simulation and emission modeling system which aims at quantifying the effects of different types of traffic calming measures on vehicle emissions both at a link-level and at a network-level. It also investigates the effects of isolated traffic-calming measures at a corridor level and area-wide calming schemes, using a scenario analysis. Our study is set in Montreal, Canada where a traffic simulation model for a dense urban neighborhood is extended with capabilities for microscopic emission estimation. The results indicate that on average, isolated calming measures increase carbon dioxide (CO₂), carbon monoxide (CO), and nitrogen oxides (NO_x) emissions by 1.5, 0.3, and 1.5 %, respectively across the entire network. Area-wide schemes result in a percentage increase of 3.8 % for CO₂, 1.2 % for CO, and 2.2 % for NO_x across the entire network. Along specific corridors where traffic calming measures were simulated, increases in emissions of up to 83 % were observed. We also account for the effect of different measures on traffic volumes and observe moderate decreases in areas that have undergone traffic calming. In spite of traffic flow reductions, total emissions do increase.     

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.     

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.     

The viability of pure vegetable oil as an alternative fuel for large ships

Heavy fuels are likely to remain the dominant fuel source for two-stroke, low-speed diesel engines for large ship propulsion for the next decade or more. There is however, potential for increased use of pure vegetable oils (PVO) as an alternative and, by emitting lower levels of several pollutants, this can help the attainment of Annex VI of the MARPOL 73/78 convention aimed at large ships using fuels with less than 4.5% sulphur or 1.5% sulphur in SO_X emission control areas The use of alternative fuels can also influence the attainment of the Kyoto protocol that requires greenhouse gas emissions to be reduced by 5% by 2010 compared to 1990. This paper analyses the physical and chemical properties of various pure vegetable oils as an alternative to heavy fuel oil for large ship propulsion.     

Network-wide traffic and environmental impacts of acceleration and deceleration among Eco-Driving Vehicles in different road configurations

Eco-Driving, a driver behaviour-based method, has featured in a number of national policy documents as part of CO₂ emission reduction or climate change strategies. This investigation comprises a detailed assessment of acceleration and deceleration in Eco-Driving Vehicles at different penetration levels in the vehicle fleet, under varying traffic composition and volume. The impacts of Eco-Driving on network-wide traffic and environmental performance at a number of speed-restricted road networks (30?km/h) is quantified using microsimulation. The results show that increasing levels of Eco-Driving in certain road networks result in significant environmental and traffic congestion detriments at the road network level in the presence of heavy traffic. Increases in CO₂ emissions of up to 18% were found. However, with the addition of vehicle-to-vehicle or vehicle-to-infrastructure communication technology which facilitates dynamic driving control on speed and acceleration/deceleration in vehicles, improvements in CO₂ emissions and traffic congestion are possible using Eco-Driving.     

Experimental evaluation of Heavy Duty Vehicle speed patterns in urban and port areas and estimation of their fuel consumption and exhaust emissions

Exhaust emissions and fuel consumption of Heavy Duty Vehicles (HDVs) in urban and port areas were evaluated through a dedicated investigation. The HDV fleet composition and traffic driving from highways to the maritime port of Genoa and crossing the city were analysed. Typical urban trips linking highway exits to port gates and HDV mission profiles within the port area were defined. A validation was performed through on-board instrumentation to record HDV instantaneous speeds in urban and port zones. A statistical procedure enabled the building-up of representative speed patterns. High contrasts and specific driving conditions were observed in the port area. Representative speed profiles were then used to simulate fuel consumption and emissions for HDVs, using the Passenger car and Heavy duty Emission Model (PHEM). Complementary estimations were derived from Copert and HBEFA methodologies, allowing the comparison of different calculation approaches and scales. Finally, PHEM was implemented to assess the performances of EGR or SCR systems for NO_X reduction in urban driving and at very low speeds.The method and results of the investigation are presented. Fuel consumption and pollutant emission estimation through different methodologies are discussed, as well as the necessity of characterizing very local driving conditions for appropriate assessment.     

基于LEAP模型的佛山市交通碳排放研究

随着城市化的发展,珠三角城市交通能源消耗和碳排放迅速增长。为了探讨珠三角城市低碳交通的发展方向,本文采用LEAP模型,以珠三角的佛山市为例,模拟了不同情景下交通总量、陆运和水运的能源消耗、能源结构和碳排放由2011至2030年的变化情况;并据此提出了珠三角城市低碳交通发展对策。结果表明:水运在交通运输中所占份额逐渐被陆运替代,将形成陆运为主、水运为辅的交通模式;在交通总量、陆运和水运等的交通能耗及碳排放方面,低碳情景均小于基准情景,且呈水运小于陆运的态势;而清洁能源使用比重的增加则有利于交通领域的低碳发展。珠三角城市低碳交通发展需关注陆运交通,提高清洁能源在陆运中的使用比重,优化陆运与水运的交通布局,提高运输及能源利用效率。     

A model for evaluating the environmental and functional benefits of “innovative” roundabouts

This study looks at the singling out of a multi-parameter criterion for choosing conventional or innovative roundabout layouts, by taking functional, environmental and economic aspects into consideration. The performances of three conventional roundabouts (with different lane number at entries and through the ring), turbo-roundabouts and roundabouts with right-turn bypass lane on all the arms (flower roundabouts) have been compared in terms of vehicle delays and pollutant (carbon dioxide, nitrogen oxides, particle pollution (PM₁₀ and PM_2.5)) emissions. By means of closed-form capacity models and with the help of COPERT IV^© software, several traffic simulations have been carried out, referred to yearly peak flow values Q_max and ranging between 1300 and 3300 veh/h, starting from a typical annual traffic demand curve in urban areas. The estimation of cumulative vehicle delays and annual pollutant emissions, together with construction and maintenance costs has allowed working out overall costs for each roundabout under consideration, depending on the traffic demand. Thus, the proposed model allows finding the most cost-effective geometric solution as to overall costs for a comprehensive case record of traffic values.     

A tool for calculating aircraft emissions and its application to Greek airspace

This paper quantifies the impact of aircraft emissions on local air quality and climate change. Aircraft emissions during the cruise cycle and the landing/take-off cycle are considered. A tool is developed that computes emission values using real-time air traffic data derived from various databases. Emissions include carbon dioxide, hydrocarbons, carbon monoxide and nitrogen oxides. The overall output is a detailed ‘emissions map’ of a given territory that enables the identification of critical emission spots including routes, airports, season, aircraft type and flight category. The method can be used for real-time monitoring of airline emissions and for policy analysis. The proposed tool and resulting outputs are illustrated in the case of the Greek airport system using domestic, international and overflights. Demand volatility driven mainly by tourism and its impact on emissions is assessed.     

Assessing the importance of transportation activity data for urban emission inventories

The aim of this research is the implementation of a GPS-based modelling approach for improving the characterization of vehicle speed spatial variation within urban areas, and a comparison of the resulting emissions with a widely used approach to emission inventory compiling. The ultimate goal of this study is to evaluate and understand the importance of activity data for improving the road transport emission inventory in urban areas. For this purpose, three numerical tools, namely, (i) the microsimulation traffic model (VISSIM); (ii) the mesoscopic emissions model (TREM); and (iii) the air quality model (URBAIR), were linked and applied to a medium-sized European city (Aveiro, Portugal). As an alternative, traffic emissions based on a widely used approach are calculated by assuming a vehicle speed value according to driving mode. The detailed GPS-based modelling approach results in lower total road traffic emissions for the urban area (7.9, 5.4, 4.6 and 3.2% of the total PM10, NO_x, CO and VOC daily emissions, respectively). Moreover, an important variation of emissions was observed for all pollutants when analysing the magnitude of the 5th and 95th percentile emission values for the entire urban area, ranging from −15 to 49% for CO, −14 to 31% for VOC, −19 to 46% for NO_x and −22 to 52% for PM10. The proposed GPS-based approach reveals the benefits of addressing the spatial and temporal variability of the vehicle speed within urban areas in comparison with vehicle speed data aggregated by a driving mode, demonstrating its usefulness in quantifying and reducing the uncertainty of road transport inventories.     

Do new sources of traffic data make the application of Chaos Theory to traffic management a realistic possibility?

Current signal systems for managing road traffic in many urban areas around the world lack a coordinated approach to detecting the spatial and temporal evolution of congestion across control regions within city networks. This severely inhibits these systems’ ability to detect reliably, on a strategic level, the onset of congestion and implement effective preventative action. As traffic is a time-dependent and non-linear system, Chaos Theory is a prime candidate for application to Urban Traffic Control (UTC) to improve congestion and pollution management. Previous applications have been restricted to relatively uncomplicated motorway and inter-urban networks, arguably where the associated problems of congestion and vehicle emissions are less severe, due to a general unavailability of high-resolution temporal and spatial data that preserve the variability in short-term traffic patterns required for Chaos Theory to work to its full potential. This paper argues that this restriction can now be overcome due to the emergence of new sources of high-resolution data and large data storage capabilities. Consequently, this opens up the real possibility for a new generation of UTC systems that are better able to detect the dynamic states of traffic and therefore more effectively prevent the onset of traffic congestion in urban areas worldwide.     

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.