While the effects of various socio-economic factors on sound evaluation have been investigated in numerous previous studies, the aim of this study is to study the relationships between environmental noise levels and socioeconomic factors, using Greater London as acase study city.The environmental noise levels are obtained from calculated noise maps, through as eries of data processing, and 78 socio-economic factors from various GIS databases are considered at micro-and macro-scales, namely at neighbourhood and borough levels. It is shown that the noise levels of neighbourhoods and boroughs in London have close relationships with anumber of socioeconomic factors. At the neighbourhood level, generally speaking, an area with ahigher noise leveltends to be among the more deprivedinEngland, especially in terms of health, barriers to housing and services, and living environment. There are more people with bad health status, and less people looking after home or family.I ti s interesting to note that the neighbourhood noise levels are not significantly correlated with the percentages of various religious communities, total number of benefits claimants, and with resident population and male/female resident ratio. As expected, non-domestic building and roads are more likely to be found in noisier neighbourhoods. More students live in noisier neighbourhoods, whereas residents who work part-time may tend to live in quieter areas. At the borough level, with ahigher noise level, more adults aged 20-44, and less children and teenagers might tend to live there, and the income leveli sg enerally higher.E nvironmental noise levels have positive relationships with the population density and total population change, and negative correlations with the total fertility rate and death rate. The correlations between noise levels and academic attainments of school children are not significant. While the noise levels might be related to the labour market to acertain extent, for the employment and unemployment rates, no significant correlation has been shown with the borough noise levels. size/type, family size, education level, income and the economic status, length of residence, type of occupancy, marital status, cultural differences, lifestyle and weather on noise annoyance [3,4,5,6,7,8,9,10,11,12]. However,p revious studies were generally based on questionnaire surveyswith sampled individuals or households, and the results were often limited to arestricted range of areas and the socio-economic factors considered were also often limited.Recently large scale strategic noise mapping has become an essential requirement, especially in Europe [13,14,15], and corresponding software/ techniques have been widely used in practice for noise strategies and policies [16,17,18,19]. An oise map, typically in af orm of interpolated iso-contours, is away of presenting geographical distribution of noise exposure, either in terms of calculated or measured levels [20]. Whilst there are still various attempts to improve the accuracy, computing-based noise ...