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Title: How can road traffic induced COâ‚‚ be reduced 60% from its current level in Norwich, U.K. by 2025?
Author: Nejadkoorki, Farhad.
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2006
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In the UK, transportation is the cause of a quarter of total Carbon dioxide (C02) emissions and road transport contributes 85% of this. This thesis seeks to examine the ways in which the road traffic induced CO2 can be reduced in Norwich city, UK. In order to estimate and model the emissions a Micro Scale Approach (MiSA) is used by coupling a road traffic model (SATURN), with a Geographical Information system (ArcGIS) and mathematical calculation software (MATLAB). This thesis estimates CO2 emissions on a street by street resolution using SATURN to model traffic conditions, MATLAB for emission calculations and a GIS for visualization. It was found that total CO2 emissions were 69105 tonnes in 2003 and a business as usual scenario indicated that these are likely to rise to 79912 tonnes by 2025. The key driver of this increase appeared to be population growth, with increases in personal mobility and improvements in vehicle efficiency cancelling each other out. This study demonstrates how the road traffic induced CO2 emissions can be reduced in Norwich from their current levels by 2025 using a variety of scenarios. The largest reduction (32%-33%) was where 60% of cars were displaced by pedal cycles or buses. The second largest reduction (24%) occurred through a technological improvement scenario assuming 50% more improvements than the expected levels by 2025. The third largest reduction (21%) was achieved by reducing personal mobility by 37.3%. One aim of this thesis was to see whether a 60% cut was feasible and the results indicated that there was no single scenario able to reduce emissions by this amount. Consequently, the scenarios were combined and a mix of reducing personal mobility by 37.3% and switching from cars to non-motorized vehicles or walking (60%) is likely to be the best way to achieve this, leading to a 53% reduction in CO2 emissions.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available