Prediction and reduction of traffic pollution in urban areas
This thesis is the result of five years research into road traffic emissions of air pollutants. It includes a review of traffic pollution studies and models, and a description of the PREDICT model suite and PREMIT emissions model. These models were used to evaluate environmentally sensitive traffic control strategies, some of which were based on the use of Advanced Transport Telematics (ATT). This research has improved our understanding of traffic emissions. It studied emissions of the following pollutants: carbon monoxide (CO), hydrocarbons (HC) and oxides of nitrogen (NOx). PREMIT modelled emissions from each driving mode (cruise, acceleration, deceleration and idling) and, consequently, predicted relatively complex emission characteristics for some scenarios. Results suggest that emission models should represent emissions by driving mode, instead of using urban driving cycles or average speeds. Emissions of NOx were more complex than those of CO and HC. The change in NOx, caused by a particular strategy, could be similar or opposite to changes in CO and HC. Similarly, for some scenarios, a reduction in stops and delay did not reduce emissions of NOx. It was also noted that the magnitude of changes in emissions of NOx were usually much less than the corresponding changes in CO and HC. In general, the traffic control strategies based on the adjustment of signal timings were not effective in reducing total network emissions. However, high emissions of pollutants on particular links could, potentially, be reduced by changing signal timings. For many links, mutually exclusive strategies existed for reducing emissions of CO and HC, and emissions of NOx. Hence, a decision maker may have to choose which pollutants are to be reduced, and which can be allowed to increase. The environmental area licensing strategy gave relatively large reductions in emissions of all pollutants. This strategy was superior to the traffic signal timing strategies because it had no detrimental impact on the efficiency of the traffic network and gave simultaneous reductions in emissions of CO, HC and NOx.