Exploring the use of mobile sensors for noise and black carbon measurements in an urban environment

Mobile measurements have been collected on a bicycle equipped with a global positioning system (GPS) in a few connecting streets in Gent (Belgium). The 1-s sound pressure levels and 1-s black carbon concentrations were measured. In addition, 5 continuous monitoring fixed stations connected to building facades were used. Different processing methods are compared, based on different temporal and spatial weighting aggregations. The possibility to take profit of the fixed stations to refine estimations is tested, according to the noise levels collected at fixed stations and the distance between mobile and fixed sensors. In a last step, route selection based on travel distance, noise levels and black-carbon measurements is explored based on the data obtained

Towards traffic situation noise emission models

This article proposes a methodology to account for vehicle kinematics in a fast and efficient way when using single vehicle noise emission models such as the Harmonoise/Imagine, Nord2000 or NMPB. A model is built, which mimics the traffic situation emission models developed in the field of airborne pollutants research. The model aggregates the sound power emitted over driving cycles which are statistically representative of real-world driving conditions. Four different driving conditions are included in the cycles, ranging from free-flowing to stop-and-go traffic conditions. The sound power levels estimated with this new approach are significantly different from the ones estimated with the mean speed approach recommended by the noise mapping guidelines, especially when traffic is congested, suggesting that the method could prove relevant for improving noise map accuracy, in particular in urban context

Sound pleasantness evaluation of pedestrian walks in urban sound environments

ICA 2016, 22nd International Congress on Acoustics, BUENOS AIRES, ARGENTINE, 05-/09/2016 - 09/09/2016The health benefits of a daily physical activity, and of walking in particular, are widely acknowledged. However, walking in urban environment inevitably leads to an increased exposure to noise, which forms a drawback of choosing this transportation mode. Being able to estimate the sound pleasantness associated with an urban walk trip has many potential applications, such as informing pedestrians about the sound along their intended walk, which may help them to optimize their route choice. In the past decade, various studies have focused on characterizing and estimating the sound pleasantness perceived at specific locations, on the basis of perceptive and physical measurements. However, to estimate the sound pleasantness along an urban walking trip, an additional step is required, which consists of assessing how a pedestrian evaluates the overall pleasantness of a sound environment that varies along the walking trip. In this work, the results of two laboratory experiments and one field experiment are discussed, which were designed to assess the overall evaluation of the sound environment along an urban walk. Physical and perceptive measurements at specified positions or continuously along a series of tested routes are available, in addition to a global evaluation of the route. A comparison between the results of the three experiments provides a rich source of information to understand how the sound pleasantness of a pedestrian walk is evaluated. The main conclusion is that for short walks (of about 1 minute), a recency effect is observed, which tends to disappear when the duration of the walk increases

Comparison of noise indicators in an urban context

Inter-Noise 2016, 45th International Congress and Exposition of Noise Control Engineering, HAMBOURG, ALLEMAGNE, 21-/08/2016 - 24/08/2016Noise is a major environmental issue, which gave birth in the last decades to the development of many engineering methods dedicated to both its estimation and mitigation. The specificity of the noise pollution problem lies in the complexity of human hearing and subjective assessment, and in the high spatiotemporal variation and rich spectral content of the noise generated by a wide variety of sources in urban context. Indicators that encompass all these dimensions are required for the description of sound environments and for the evaluation of noise mitigation strategies. This paper compares usual and more specific indicators, dedicated to environmental noise analyses, by means of a literature review. The comparison is based on the three following criteria: i) the ability of indicators to describe and physically categorize the urban sound environments, ii) the relevance of indicators for describing the perceptive appreciations of urban sound environments, iii) the ability of indicators to be estimated through classical or more advanced traffic noise estimation models. A discussion compares the pro and cons of the selected indicators in an operational scop

Influence of experimental conditions on sound pleasantness evaluations

ICA 2016, 22nd International Congress on Acoustics, BUENOS AIRES, ARGENTINE, 05-/09/2016 - 09/09/2016Being able to characterize and estimate the urban sound perception is a key point to improve the city dwellers environmental quality. In the past decade, various studies have focused on collecting perceived global sound pleasantness at specific locations. Some of them were carried out on field in order to evaluate the soundscape perception of the participants directly in their context. Other studies were realized in laboratory to better control the stimuli and to increase the number of participants who were subjected to the same sound environment. Most of the laboratory experiments are done in large or semi-anechoic chamber with calibrated and highly realistic audio reproduction in order to respect the ecological validity of the experiment. On one hand, even with a high immersive level, the laboratory context is not as rich as the field context and the two types of experiment could lead to different results. On the other hand, few studies exist showing the influence of decreasing ecological validity for the same experience. This work presents a short statistical analysis of perceptive evaluations of ten urban locations under 4 different test conditions. First, evaluations are carried out directly in-situ in the city of Paris. Then audio-visual recordings of these locations are evaluated in three different experimental conditions: (i) in a well-controlled acoustic laboratory in Paris region with French people, (ii) in an acoustic laboratory in Buenos Aires with Argentinean participants and lowest immersive conditions, (iii) in a habitational room with Argentinean participants and subjective calibration. The study reveals that both the 'country' factor and the experimental conditions in laboratory do not show any significant impact on the perceived sound pleasantness and perceived loudness assessments

Data mining on urban sound sensor networks

ICA 2016, 22nd International Congress on Acoustics, BUENOS AIRES, ARGENTINE, 05-/09/2016 - 09/09/2016Urban sound sensor networks deliver megabytes of data on a daily basis so the question on how to extract useful knowledge from this overwhelming dataset is eminent. This paper presents and compares two extremely different approaches. The first approach uses as much as possible expert knowledge on how people perceive the sonic environment, the second approach simply considers the spectra obtained every time step as meaningless numbers yet tries to structure them in a meaningful way. The approach based on expert knowledge starts by extracting features that a human listener might use to detect salient sounds and to recognize these sounds. These features are then fed to a recurrent neural network that learns in an unsupervised way to structure and group these features based on co-occurrence and typical sequences. The network is constructed to mimic human auditory processing and includes inhibition and adaptation processes. The outcome of this network is the activation of a set of several hundred neurons. The second approach collects a sequence of one minute of sound spectra (1/8 second time step) and summarizes it using Gaussian mixture models in the frequency-amplitude space. Mean and standard deviation of the set of Gaussians are used for further analysis. In both cases, the outcome is clustered to analyze similarities over space and time as well as to detect outliers. Both approaches are applied on a dataset obtained from 25 measurement nodes during approximately one and a half year in Paris, France. Although the approach based on human listening models is expected to be much more precise when it comes to analyzing and clustering soundscapes, it is also much slower than the blind data analysis