Abstract

Policy developments in the UK and the European Union (EU) now require local authorities to engage the general public within the whole process of local air quality management (AQM). Indeed, this is considered to be one of the means by which air quality issues can gain public support and help ensure future improvements. One of the outcomes of this is that data sets associated with air quality management must now be disseminated to nonscientific audiences. This is a problematic task for a number of reasons. One of these relates to the fact that air quality data are complex and variable, yet the public demand representations that are clear and unambiguous. Another important issue is associated with the increasing use of geographical information systems (GIS) and mapping tools, which allow data to be generated and summarised in many different ways without due regard to the effects that the choice of methodology can have on the way data are interpreted. The variation in information obtained using different techniques can represent a problem, but is also an opportunity to further explore data sets and to draw out specific information for complementary air quality management tasks. However, at present, the lack of a well-grounded methodology and guidance for handling and representing the spatial aspects of data sets means that consistency between areas and authorities is not maintained. Such a situation fosters ambiguity at several levels, from the individual's perception of public health-related information to an Authority's rationale for the selection of air quality management areas (AQMAs). This paper investigates a number of issues relating to spatial data generation and representation in the field of air quality management, particularly in relation to emissions inventory data. The examples are UK based, but the issues raised are applicable to other examples and areas. One case study examines the difference in information gained through a number of common mapping techniques and shows how different ‘problems’ can be identified merely as an artefact of the dissemination technique itself. To further illustrate the difficulties and conflicts faced in representing and explaining these data in a practical context, reference is then also made to the methods recently considered by an example London authority. The paper concludes with a call for the development of a more standardised method for representing different types of air quality management-related data, which may help to overcome these problems in the future.

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