The impacts of traffic calming measures on vehicle exhaust emmissions.
Boulter, Paul Graeme (2001) The impacts of traffic calming measures on vehicle exhaust emmissions. PhD thesis, Middlesex University..
This Thesis describes a study of the impacts of traffic calming on exhaust emissions, the most detailed and extensive of its kind to date. The main objectives of the work were to measure the effects of different types of traffic calming measure on vehicle emissions, to develop a system of comparative performance indicators and guidance for local authorities, and to assess and improve the performance of an existing micro-scale emission model in traffic calming applications. There were several elements to the research which have not previously been reported, including the development of driving cycles for traffic calming based on external speed measurements and the use of remote sensing to assess the impacts of traffic calming on emissions in situ. Nine different types of measure were investigated, including a mixture of vertical deflections (e.g. road humps, speed cushions) and horizontal deflections (e. g. chicanes). Driving cycles were formulated to represent vehicle operation before and after the introduction of the schemes, based on traffic speeds measured using both an instrumented car and an external method (LIDAR). Fuel consumption and emissions of CO, HC, NOx, and C02 from a total of 22 cars (including petrol non-catalyst, petrol catalyst, and diesel vehicles) were measured on a chassis dynamometer using the cycles. Emissions of total particulate matter were also recorded from the diesel vehicles. The results from the laboratory emission tests were used to compare the performance of an 'average speed' emission model (MEET) and a 'modal' emission model (MODEM). Also, an attempt was made to improve the accuracy of MODEM model in such applications by developing a variant model (MODEM-TC) for use in traffic calming applications. In MODEM-TC the original MODEM emission matrices were replaced with ones derived from the laboratory test results. The emission tests indicated that traffic calming increases exhaust emissions. For the three types of car tested, emissions of CO, HC, and C02 increased by between 20% and 60%. Only the diesel cars showed a substantial (30%) and statistically significant increase in NOx emissions. Emissions of total particulate matter from diesel cars also increased by 30%. The more 'severe' traffic calming measures (e.g . road humps) tended to result in the greatest speed reductions and some of the largest increases in emissions. The 50-73% increase in mass emissions of CO per kilometre (for all vehicles) determined by remote sensing agreed reasonably well with the range of impacts measured in the laboratory emission tests, but the remote sensing HC results were less conclusive. For almost all combinations of vehicle type and pollutant, the MEET model provided a more reliable indication of the likely impact of traffic calming than the MODEM and MODEM-TC models, in spite of the fact that the latter employ a more detailed mechanism for representing vehicle operation. It was concluded that the most fundamental Problem with modal models is that the analyser emission signals on which they are based are delayed and damped relative to the 'true' signal. .It appears that further advances in the field of modal emission modelling will not be forthcoming until realistic continuous emission data are available. Other workers are currently developing a mathematical model of the measurement system which can be used to reconstruct the original emission signal in the exhaust pipe from the one measured at the analyser.
|Item Type:||Thesis (PhD)|
A Thesis submitted to Middlesex University in partial fulfilment of the requirements for the degree of Doctor of Philosophy.
|Research Areas:||B. > Theses|
|Deposited On:||02 Nov 2010 16:42|
|Last Modified:||13 Nov 2014 21:46|
Repository staff only: item control page
Full text downloads (NB count will be zero if no full text documents are attached to the record)
Downloads per month over the past year