Airports are often located near densely populated residential areas, affecting a large number of people. Thus, knowing socio-demographic characteristics of the noise-affected areas is important for the development of policies on noise control and abatement. This study proposes a new methodology that combines airport noise models with spatial statistics and geographical information systems to identify spatial clusters of socio-demographic characteristics in relationship to the noise level. Statistically significant ‘hot’ and ‘cold’ socio-demographic clusters represent spatial concentrations of certain social groups, corresponding to various levels of vulnerability to environmental impacts. Results show that the population ‘paying’ for the cost of noise from Logan International Airport in Boston, USA, is highly vulnerable as there are more minority and lower-income populations, and lower house prices in the noise-affected areas. These results should draw the attention of policy-makers and the public as policies for noise abatement are being developed.
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