Demonstrating Techniques for Air Pollution Source Performance Assessment

Measurements of ambient air-quality have been made routinely in the UK for many decades. The number of measurements has expanded substantially in the past decade following the implementation of the National Air Quality Strategy. This has increased the number of sites and pollutants measured and the number of local meteorological records taken to help interpret air-quality data. The collected air-quality data are generally used to check if the local pollution climate complies with air-quality standards. For this purpose they are summarised as annual statistics e.g. as annual-average concentrations, or as the total hours per year above a designated concentration value. Although such statistics serve to check compliance, they only use part of the information embedded in the air-quality and meteorological data for the purpose of assessing the performance of sources and policies. There have been several attempts to make better use of routine air-quality monitoring data for purposes for tracking the performance of individual sources and for managing air-quality more effectively. Although such studies have shown the advantages of better methods for presenting and interpreting data (e.g. polar plots of concentrations and wind speed) these advantages have not been generally recognised or the methods transferred into regular use by practitioners. This is in spite of the fact that such information would lead to more robust, rapid and cost-effective decisions for air quality management. Furthermore, few attempts have been made to apply novel forms of aerometric analysis to modelled data. When comparing predictions against observations it is important to check that a model 'gives the right answer for the right reasons'. Opportunities now exist to subject the latest generation of 'one atmosphere' models to rigorous forms of aerometric evaluation. This knowledge transfer proposal therefore aims to demonstrate the advantages of 'smarter' forms of aerometric analysis to a wide range of air-quality practitioners. We will show these advantages in a range of practical air-quality situations both for traditional community pollutants (e.g. SO2, NO2, PM10) and 'new priority pollutants' (e.g. methane) so that such methods become established in regular use. We will show how existing and novel techniques can be used to exploit air-quality data more fully and rigorously, and crucially how the extra information can benefit operational and policy decisions e.g. by giving earlier and clearer advice on the performance of individual sources, or on the progress of specific policies. The methods will not only enable measured concentrations to be better exploited, but will also be applied to modelled concentrations - so helping to improve prediction and management of air quality in future. We will disseminate our methods to practitioners via a range of mechanisms including (i) a website for announcements, progress reports and archived resources, (ii) case summaries & evaluation meetings, (iii) handouts & presentations to user bodies, (iv) conference posters/papers, (v) peer-reviewed publications, (vi) a final report and (vi) a closing workshop. In order to transfer the methods into regular use, we will show users that they can inform practical decisions on air quality (e.g. in management areas), resource use (e.g. fuels, abatement costs), societal behaviours (e.g. on transport, waste), health, (e.g. particulates) and quality of life. Our team has well-established links to professional air-quality bodies including: the Institute of Air-Quality Management, the UK's Atmospheric Dispersion Modelling Liaison Committee, and Environmental Protection UK / with its specialist Dispersion Modellers' User Group. We will use these links to consult on the selection of cases studies, to give information on project progress, and to show air-quality practitioners how their decisions can benefit from improved air-quality analysis techniques.