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Assessment of the relationship between industrial and traffic sources contributing to air quality objective exceedences: a theoretical modelling exercise

In the UK, local government is under a statutory duty to undertake scientific review and assessment of air quality and designate Air Quality Management Areas (AQMAs) in locations with identified air quality problems. This paper investigates, from a theoretical perspective, a situation where traffic...

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Published in:Environmental modelling & software : with environment data news 2006-04, Vol.21 (4), p.494-500
Main Authors: Leksmono, N.S., Longhurst, J.W.S., Ling, K.A., Chatterton, T.J., Fisher, B.E.A., Irwin, J.G.
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description In the UK, local government is under a statutory duty to undertake scientific review and assessment of air quality and designate Air Quality Management Areas (AQMAs) in locations with identified air quality problems. This paper investigates, from a theoretical perspective, a situation where traffic is not the sole cause of an AQMA declaration. It presents air quality assessments in different scenarios, which are modelled using ADMS-Urban to predict concentrations of nitrogen dioxide. Modelling is carried out using simple scenarios with a combination of traffic and industrial emissions, different type of roads, meteorological data and approaches to derive nitrogen dioxide from oxides of nitrogen. The modelling results have shown the significance of the NO x :NO 2 relationship and meteorological data as parameters inputted into the model. The results are discussed and compared with the guidance provided by Department for Environment, Food and Rural Affairs (Defra). Examples of local authorities' source apportionment studies are presented.
doi_str_mv 10.1016/j.envsoft.2004.07.012
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ispartof Environmental modelling & software : with environment data news, 2006-04, Vol.21 (4), p.494-500
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subjects ADMS-Urban
Air quality management
Industrial pollution
NO x:NO 2 relationship
Theoretical modelling
Traffic pollution
title Assessment of the relationship between industrial and traffic sources contributing to air quality objective exceedences: a theoretical modelling exercise
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