The importance of accurate and representative air quality impact assessment (AQIA) for new developments is becoming increasingly focal with the introduction of the framework for Local Air Quality Management (Air Quality Management Areas and Air Quality Action Plans), stricter legislative requirements and increasing traffic flows. It is argued in this thesis that incorporation of workforce profile variables (WPVs) will allow a more detailed site-specific air quality assessment to be undertaken. Workforce Profile Variables included within this research include Region, Specific Location, Socio-economic Grouping, Gender and Age. The findings from this work enable an evaluation of whether such variables should be included in AQIAs for employment related developments. The research examines the effect of including region, specific location and WPVs (age, gender and socio-economic grouping) in commuter emissions prediction and the need for inclusion of such variables in AQIA for new employment related developments. Such WPVs are not considered in conventional AQIA and therefore results from this work are compared with conventional techniques. In order to achieve this, two models have been developed which inter-relate specific data from the UK National Travel Survey and emission factors. The models predict emissions impact (RACE) and traffic generation (TRACE) and have been applied to three case study scenarios in the UK, covering a range of employment related development scenarios in London, Bath and Devon. The TRACE element of the research has incorporated atmospheric dispersion modelling in order to derive pollutant concentrations and allow comparison with the conventional approach to AQIA. The findings associated with the RACE element of the research show that region, specific location and WPVs can influence emission predictions associated with commuting. The outcomes from the TRACE comparison show that lower pollutant concentrations are likely from the inclusion of WPVs, when compared with the conventional approach to AQIA. The significance of these differences is dependent upon existing pollutant concentrations in the local area. Greatest differences are seen for predictions of nitrogen dioxide and these become more significant in: areas with existing concentrations either close to or exceeding air quality objectives. The research also demonstrates how inclusion of such variables allows more site specific assessment. It is concluded that the inclusion of WPVs will lead to greater confidence in air quality predictions associated with new employment related developments and make such assessments more site-specific.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:495518 |
| Date | January 2008 |
| Creators | Davey, Nicholas Edward |
| Publisher | University of the West of England, Bristol |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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