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Mapping ambient urban air pollution at the small area scale : a GIS approach

Smallbone, Kirsty Louise (1998) Mapping ambient urban air pollution at the small area scale : a GIS approach. Doctoral thesis, University of Huddersfield.

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    Air pollution is an emotive and complex issue, affecting materials, vegetation
    growth and human health. Given that over half the world's population live
    within urban areas and that those areas are often highly polluted, the ability to
    understand the patterns and magnitude of pollution at the small area (urban
    environment) level is increasingly important. Recent research has highlighted,
    in particular, the apparent relationship between traffic-related pollution and
    respiratory health, while the increasing prevalence of asthma, especially
    amongst children, has been widely attributed to exposure to traffic-related air
    pollution. The UK government has reacted to this growing concern by
    publishing the UK National Air Quality Strategy (DOE 1996) which forces all
    Local Authorities in England and Wales to review air quality in their area and
    designate any areas not expected to meet the 2005 air quality standards as Air
    Quality Management Areas (AQMAs), though what constitutes AQMAs and
    how to define them remains vague.

    Against this background, there is a growing need to understand the patterns and
    magnitude of urban air pollution and for improvements in pollution mapping
    methods. This thesis aims to contribute to this knowledge. The background to
    air pollution and related research has been examined within the first section of
    this report. A review of sampling methods was conducted, a sampling strategy
    devised and a number of surveys conducted to investigate both the spatial
    nature of air pollution and, more specifically, the dispersion of pollution with
    varying characteristics (distance to road, vehicle volume, height above ground
    level etc). The resultant data was analysed and a number of patterns identified.
    The ability of linear dispersion models to accurately predict air pollution was
    also considered. A variety of models were examined, ranging from the
    simplistic (e.g. DMRB) to the more complex (e.g. CALINE4) model. The
    model best able to predict pollution at specific sites was then used to predict concentrations over the entire urban area which were then compared to actual
    monitored data. The resultant analysis, indicated that the dispersion model is
    not a good method for predicting pollution concentrations at the small area
    level, and therefore an alternative method of mapping was investigated. Using
    the ARC/INFO geographical information system (GIS) a regression analysis
    approach was applied to the study area. A number of variables including
    altitude, landuse type, traffic volume and composition etc, were examined and
    their ability to predict air pollution tested using data on nitrogen dioxide from
    intensive field surveys. The study area was then transformed into a grid of
    10m2, regression analysis was performed on each individual square and the
    results mapped. The monitored data was then intersected with the resultant
    map and monitored and modeled concentrations compared. Results of the
    analysis indicated that the regression analysis could explain up to 61 per cent of
    the variation in nitrogen dioxide concentrations and thus performed
    significantly better than the dispersion model method. The ease of application
    and transferability of the regression method means it has a wide range of
    applied and academic uses that are discussed in the final section.

    Item Type: Thesis (Doctoral)
    Additional Information: EThOS Persistent ID
    Uncontrolled Keywords: Dispersion modelling, Exposure Air Pollution
    Subjects: G Geography. Anthropology. Recreation > G Geography (General)
    G Geography. Anthropology. Recreation > GE Environmental Sciences
    Schools: School of Applied Sciences
    Depositing User: Graham Stone
    Date Deposited: 17 Jun 2009 12:37
    Last Modified: 28 Jul 2010 19:38


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