Green and calm: Modeling the relationships between noise pollution propagation and spatial patterns of urban structures and green covers

Abstract The mechanism of noise pollution propagation is considerably affected by 1) the type and configuration of its receiving environment and 2) the distance that sound waves pass to reach that environment. This study adopts a spatio-statistical approach to quantify and model associations between noise pollution levels and landscape metrics of land categories (built-up structures and urban green covers). Accordingly, noise levels were measured employing a sound pressure meter to quantify equivalent levels (Leq in dB A), in addition to their corresponding percentiles (L10 and L90). A collection of 30 sampling points were selected to measure noise data within the fall season and between 4 p.m. and 8 p.m. hours of the day. A hierarchical distance-sampling framework based on buffer areas with different radius (300 m, 600 m and 1 km) around each sampling point was compiled to measure composition and configuration metrics of land categories within each buffer area. The results derived from Pearson correlation analysis and multiple-linear regression models indicated that there is a distance-dependent relationship between the metrics of green areas and noise levels. We didn’t find remarkable distance-dependency between built-up structures and noise levels. Based on our new spatio-statistical approach, we conclude that more connected and compacted pattern of green areas closer to pollution centers can significantly alleviate the effects of noise propagation mechanism and appropriate pattern of built-up areas follows a low density distribution with coming green areas in between. Findings of this study highlight the potential of landscape ecology approach as an effective planning paradigm for designing greener and calmer cities.

[1]  Stuart H. Gage,et al.  Connecting soundscape to landscape: Which acoustic index best describes landscape configuration? , 2015 .

[2]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[3]  R. Klæboe,et al.  The impact of an adverse neighbourhood soundscape on road traffic noise annoyance , 2005 .

[4]  Eric J. Gustafson,et al.  Quantifying Landscape Spatial Pattern: What Is the State of the Art? , 1998, Ecosystems.

[5]  U. Franck,et al.  Traffic-induced noise levels in residential urban structures using landscape metrics as indicators , 2014 .

[6]  E. Murphy,et al.  Estimating human exposure to transport noise in central Dublin, Ireland. , 2009, Environment international.

[7]  Jeong Chang Seong,et al.  Spatio-temporal patterns of road traffic noise pollution in Karachi, Pakistan. , 2011, Environment international.

[8]  B. Amiri,et al.  Scenario-based evaluation of urban development sustainability: an integrative modeling approach to compromise between urbanization suitability index and landscape pattern , 2015, Environment, Development and Sustainability.

[9]  Anne Vernez Moudon,et al.  Real noise from the urban environment: how ambient community noise affects health and what can be done about it. , 2009, American journal of preventive medicine.

[10]  Ulrich Franck,et al.  Assessing modelled outdoor traffic-induced noise and air pollution around urban structures using the concept of landscape metrics , 2014 .

[11]  A. Salmanmahiny,et al.  Evaluating the strategy of decentralized urban land-use planning in a developing region , 2015 .

[12]  A. Gidlöf-Gunnarsson,et al.  Noise and well-being in urban residential environments: The potential role of perceived availability to nearby green areas , 2007 .

[13]  Jian Kang,et al.  Acoustic comfort evaluation in urban open public spaces , 2005 .

[14]  Jian Kang,et al.  Spatiotemporal variability of soundscapes in a multiple functional urban area , 2013 .

[15]  A. Asgarian,et al.  Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach , 2014, Urban Ecosystems.

[16]  B. Amiri,et al.  Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran , 2015 .

[17]  Fernando Augusto de Noronha Castro Pinto,et al.  Noise mapping of densely populated neighborhoods--example of Copacabana, Rio de Janeiro-Brazil. , 2008 .

[18]  Bahreyni Tousi Seyed Mohammad Hossein,et al.  Noise Pollution and Traffic Noise Index on Mashhad Main Streets during the Busiest Hours of Summer , 2005 .

[19]  Bruce T. Milne,et al.  Indices of landscape pattern , 1988, Landscape Ecology.

[20]  M. L. Martin,et al.  Strategic noise map of a major road carried out with two environmental prediction software packages , 2010, Environmental monitoring and assessment.

[21]  Luis Diaz-Balteiro,et al.  Noise pollution mapping approach and accuracy on landscape scales. , 2013, The Science of the total environment.

[22]  J. Schipperijn,et al.  Tools for mapping social values of urban woodlands and other green areas , 2007 .

[23]  Kevin McGarigal,et al.  Parsimony in landscape metrics: Strength, universality, and consistency , 2008 .

[24]  Carl Smith,et al.  An analysis of landscape penetration by road infrastructure and traffic noise , 2012, Comput. Environ. Urban Syst..

[25]  Léa Cristina Lucas de Souza,et al.  Urban indices as environmental noise indicators , 2011, Comput. Environ. Urban Syst..