An approach for developing road traffic noise annoyance prediction model

The main objective of "Assessment and Management of Environmental Noise (2002/49/EC)" Directive (The European Parliament and The Council of The European Union, 2002) is to define a common approach intended to avoid, prevent or reduce the harmful effects, including annoyance, due to exposure to environmental noise. To that end, noise mapping, informing the public and action planning shall be implemented. The term, 'annoyance' is defined in the Directive as 'the degree of community noise annoyance as determined by means of field surveys'. Lden and Lnight are defined as noise indicators for annoyance and for sleep disturbance, respectively. Noise annoyance dose-effect relations are to be established for these given indicators. It is stated in the Directive that each action plan should contain estimates in terms of reduction in number of people annoyed and sleep disturbed. Although the main purpose of the Directive and of noise control studies over the world is to reduce noise annoyance, the implementation is focused mostly on reducing noise levels, not annoyance, because annoyance levels are directly linked to noise levels in dose-effect relationships. Dose-effect relationships linking Lden and Lnight noise indicators to annoyance levels are provided by European Commission Working Groups. The dose-effect relationships were created from socio-acoustic surveys, made in countries of North Europe, North America and Australia. These relationships do not necessarily apply to other countries to consider social factors of annoyance. In some studies it is concluded that in dose effect relationships, social, psychological or economic factors, are far more important than acoustic or physical factors. On the other hand, many studies have shown that the indicators used, such as A-weighted values or Lden and Lnight, do not reflect many aspects of annoyance. A more efficient and accurate way to determine annoyance might be to eliminate global noise indicators and to create local models which use all the information collected for noise mapping as input, and provide annoyance levels as a direct output, taking into account physical and non-physical factors. To that end, this study is designed to create an approach for developing a road traffic noise annoyance prediction model. This approach allows authorities to develop their own annoyance prediction models, taking into account characteristics of traffic, urban development and population. The objective of this approach is to create an accurate local road traffic noise annoyance prediction model which considers not only acoustical aspects but also social aspects, without using noise indicators. The approach to develop the model includes well known methods such as noise maps, socio-acoustic surveys, sound insulation measurements, sound recordings and listening tests. Using all of these methods together, provides detailed information on noise sources, urban propagation conditions and people's responses to certain types of noise heard inside their homes, which help to create an accurate model. Using an accurate annoyance prediction model may provide cost effective action plans which focus on decreasing annoyance levels, and not only noise levels. Planning actions against annoyance may be easier to organize because the model helps to understand the factors which effect annoyance levels. There are some limitations to this approach. The approach is only for road traffic noise sources, but further studies may be used to implement the approach for other noise sources. This approach is for general noise annoyance and not sleep disturbance, because this study does not include awakening, motility or health effects. Meteorological effects are not taken into account because of the negligible attenuation in urban conditions. In this thesis, the approach is implemented to create an annoyance prediction model in the urban area of Besiktas in Istanbul city of Turkey, for road traffic noise. All the steps of the approach, noise maps, socio-acoustic surveys, sound insulation measurements, sound recordings, sound clips and listening tests are used to develop and to validate the model.