Impact of traffic management on black carbon emissions: a microsimulation study

This paper investigates the effectiveness of traffic management tools, includ- ing traffic signal control and en-route navigation provided by variable message signs (VMS), in reducing traffic congestion and associated emissions of CO2, NOx, and black carbon. The latter is among the most significant contributors of climate change, and is associated with many serious health problems. This study combines traffic microsimulation (S-Paramics) with emission modeling (AIRE) to simulate and predict the impacts of different traffic management measures on a number traffic and environmental Key Performance Indicators (KPIs) assessed at different spatial levels. Simulation results for a real road network located in West Glasgow suggest that these traffic management tools can bring a reduction in travel delay and BC emission respectively by up to 6 % and 3 % network wide. The improvement at local levels such as junctions or corridors can be more significant. However, our results also show that the potential benefits of such interventions are strongly dependent on a number of factors, including dynamic demand profile, VMS compliance rate, and fleet composition. Extensive discussion based on the simulation results as well as managerial insights are provided to support traffic network operation and control with environmental goals. The study described by this paper was conducted under the support of the FP7-funded CARBOTRAF project

Environmental impact of combined ITS traffic management strategies

Transport was responsible for 20% of the total greenhouse gas emissions in Europe during 2011 (European Environmental Agency 2013) with road transport being the key contributor. To tackle this, targets have been established in Europe and worldwide to curb transport emissions. This poses a significant challenge on Local Government and transport operators who need to identify a set of effective measures to reduce the environmental impact of road transport and at the same time keep the traffic smooth. Of the road transport pollutants, this paper considers NOx, CO2 and black carbon (BC). A particular focus is put on black carbon, which is formed through incomplete combustion of carboneous materials, as it has a significant impact on the Earth’s climate system. It absorbs solar radiation, influences cloud processes, and alters the melting of snow and ice cover (Bond et al. 2013). BC also causes serious health concerns: black carbon is associated with asthma and other respiratory problems, heart attacks and lung cancer (Sharma 2010; United States Environmental Protection Agency 2012). Since BC emissions are mainly produced during the decelerating and accelerating phases (Zhang et al. 2009), ITS actions able to reduce stop&go phases have the potential to reduce BC emissions. This paper investigates the effectiveness of combined ITS actions in urban context in reducing CO2 and BC emissions and improving traffic conditions

CARBOTRAF: A decision Support system for reducing pollutant emissions by adaptive traffic management

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses all these model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

An assessment of VMS-rerouting and traffic signal planning with emission objectives in an urban network — A case study for the city of Graz

This paper discusses a case study evaluating the potential impact of ITS traffic management on CO 2 and Black carbon tailpipe emissions. Results are based on extensive microsimulations performed using a calibrated VISSIM model in combination with the AIRE model for calculating the tailpipe emissions from simulated vehicle trajectories. The ITS traffic management options hereby consist of easily implementable actions such as the usage of a variable message sign (VMS) or the setting of fixed time signal plans. Our simulations show that in the current case shifting 5% of vehicles from one route to another one leads to an improvement in terms of emissions only if the VMS is complemented with an adaptation of the signal programs, while the VMS sign or the change of the signal plans alone do not yield benefits. This shows that it is not sufficient to evaluate single actions in a ceteris paribus analysis, but their joint network effects need to be taken into account

Air quality impact of a decision support system for reducing pollutant emissions: CARBOTRAF

Traffic congestion with frequent “stop & go” situations causes substantial pollutant emissions. Black carbon (BC) is a good indicator of combustion-related air pollution and results in negative health effects. Both BC and CO2 emissions are also known to contribute significantly to global warming. Current traffic control systems are designed to improve traffic flow and reduce congestion. The CARBOTRAF system combines real-time monitoring of traffic and air pollution with simulation models for emission and local air quality prediction in order to deliver on-line recommendations for alternative adaptive traffic management. The aim of introducing a CARBOTRAF system is to reduce BC and CO2 emissions and improve air quality by optimizing the traffic flows. The system is implemented and evaluated in two pilot cities, Graz and Glasgow. Model simulations link traffic states to emission and air quality levels. A chain of models combines micro-scale traffic simulations, traffic volumes, emission models and air quality simulations. This process is completed for several ITS scenarios and a range of traffic boundary conditions. The real-time DSS system uses these off-line model simulations to select optimal traffic and air quality scenarios. Traffic and BC concentrations are simultaneously monitored. In this paper the effects of ITS measures on air quality are analysed with a focus on BC

Plasmas and Controlled Nuclear Fusion

Contains reports on three research projects.U. S. Atomic Energy Commission (Contract AT(30-1)-3980

Plasmas and Controlled Nuclear Fusion

Contains reports on five research projects.U. S. Atomic Energy Commission (Contract AT(30-1)-3980