A decision support system to reducing CO2 and black carbon emissions by adaptive traffic management

Abstract

Transport sector is one of the main sources of environmental pollution and traffic congestion in urban areas. The urban air pollution affects not only human health but also ecosystem through global warming. Black carbon (BC), a product of incomplete combustion of fossil fuels, is considered as one of the main contributors of global warming. Although a lot of research has been done to investigate transport-related pollutions role on public health and air quality, further improvement and innovative ways such as applying intelligent transport systems should be developed to reduce these effects. CARBOTRAF is an European project to develop a traffic management system to implement Intelligent Traffic Systems based upon measurements and modeling of traffic, CO2 emissions, black carbon emission and local air quality. This master thesis as a part of evaluation of CARBOTRAF project, concentrated on data analysis in order to achieve three different objectives. An extensive literature review is presented in this respect and to do more practical analysis, the measured BC concentration and traffic parameters data (total flow, speed, acceleration, number of heavy vehicles and number of passenger cars) from two host cities of Glasgow, Scotland and Graz, Austria which were chosen as test sites in CARBOTRAF project, was investigated. As the first objective which is done by available data from Graz, the relation between roadside BC concentrations measured by three detectors; Graz- Nord as urban background of BC concentration,