(Review and Assessment of Commuter Emissions)
Nick Davey, March 2008
The importance of accurate and representative air quality impact prediction from new developments is increasingly becoming more important with the introduction of Air Quality Management Areas and ever tightening legislation. This research aims to explore and develop a new methodology for air quality impact prediction by examining impacts from a different dimension in order to provide greater precision in impact prediction.
The fundamental difference of the approach explored by the research is the underlying foundations of air quality impact prediction. Whereas conventional methods utilise specific factors which are applied to traffic growth irrespective of the type of people creating the impacts, the RACE approach examines the effect of including workforce-profile variables (age, gender and socio-economic grouping) in the assessment. The air quality impacts associated with transport to and from the proposed development will therefore be based on the personnel who will be occupying the development.
Early exploratory stages of the research, primarily based on the Nation Travel Survey, show that workforce-profile variables can substantially influence commuting characteristics and therefore the associated air quality impacts from commuting.
The research consists of two distinctively different research stages. Stage 1 of the research has utilised primary and secondary quantitative research in order to formulate a research model (RACE 1). This exploratory element of the research examines the effect of workforce-profile variables on EMISSIONS impact in order to establish the differences between and within the variables and allow the significance of this to be established.
Stage 2 of the research develops the first stage a step further by examining pollutant CONCENTRATIONS. Air quality impacts, in terms of concentrations, are primarily based on traffic impact characteristics, emission factors and local meteorological data. The RACE research model has therefore been developed a step further (TRACE) to enable the prediction of traffic impacts, based on workforce-profile variables, in order to allow comparison with the conventional approach. Workforce-profile derived traffic impacts from the TRACE model are based on a number of real-life case studies and will be input to the Breeze Roads and DMRB dispersion models in order to establish the effect of predicting pollutant concentrations based on people.
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