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Noise energetic indicators, like Lden, show good correlations with long term annoyance, but should be supplemented by other parameters describing the sound fluctuations, which are very common in urban areas and negatively impact noise annoyance. Thus, in this paper, the hourly values of continuous equivalent level LAeqh and the intermittency ratio (IR) were both considered to describe the urban road traffic noise, monitored in 90 sites in the city of Milan and covering different types of road, from motorways to local roads. The noise data have been processed by clustering methods to detect similarities and to figure out a criterion to classify the urban sites taking into account both equivalent noise levels and road traffic noise events. Two clusters were obtained and, considering the cluster membership of each site, the decimal logarithm of the day-time (06:00–22:00) traffic flow was used to associate each new road with the clusters. In particular, roads with average day-time hourly traffic flow ≥1900 vehicles/hour were associated with the cluster with high traffic flow. The described methodology could be fruitfully applied on road traffic noise data in other cities. [ABSTRACT FROM AUTHOR]

In addition to air pollution, environmental noise has become one of the major hazards for citizens, being Road Traffic Noise (RTN) as its main source in urban areas. Recently, low-cost Wireless Acoustic Sensor Networks (WASNs) have become an alternative to traditional strategic noise mapping in cities. In order to monitor RTN solely, WASN-based approaches should automatize the off-line removal of those events unrelated to regular road traffic (e.g., sirens, airplanes, trams, etc.). Within the LIFE DYNAMAP project, 15 urban Anomalous Noise Events (ANEs) were described through an expert-based recording campaign. However, that work only focused on the overall analysis of the events gathered during non-sequential diurnal periods. As a step forward to characterize the temporal and local particularities of urban ANEs in real acoustic environments, this work analyses their distribution between day (06:00–22:00) and night (22:00–06:00) in narrow (1 lane) and wide (more than 1 lane) streets. The study is developed on a manually-labelled 151-h acoustic database obtained from the 24-nodes WASN deployed across DYNAMAP’s Milan pilot area during a weekday and a weekend day. Results confirm the unbalanced nature of the problem (RTN represents 83.5% of the data), while identifying 26 ANE subcategories mainly derived from pedestrians, animals, transports and industry. Their presence depends more significantly on the time period than on the street type, as most events have been observed in the day-time during the weekday, despite being especially present in narrow streets. Moreover, although ANEs show quite similar median durations regardless of time and location in general terms, they usually present higher median signal-to-noise ratios at night, mainly on the weekend, which becomes especially relevant for the WASN-based computation of equivalent RTN levels.

Noise energetic indicators, like Lden, show good correlations with long term annoyance, but should be supplemented by other parameters describing the sound fluctuations, which are very common in urban areas and negatively impact noise annoyance. Thus, in this paper, the hourly values of continuous equivalent level LAeqh and the intermittency ratio (IR) were both considered to describe the urban road traffic noise, monitored in 90 sites in the city of Milan and covering different types of road, from motorways to local roads. The noise data have been processed by clustering methods to detect similarities and to figure out a criterion to classify the urban sites taking into account both equivalent noise levels and road traffic noise events. Two clusters were obtained and, considering the cluster membership of each site, the decimal logarithm of the day-time (06:00–22:00) traffic flow was used to associate each new road with the clusters. In particular, roads with average day-time hourly traffic flow ≥1900 vehicles/hour were associated with the cluster with high traffic flow. The described methodology could be fruitfully applied on road traffic noise data in other cities.

This paper presents a new multi-objective optimization formulation for the design and allocation of optimal aircraft departure routes. In the considered problem – besides two conventional objectives based on cumulative noise criteria and fuel burn – a new objective considering the flight frequency is introduced. Moreover, to take advantage of the combination of designing new routes and allocating flights to these routes, two different routes are considered simultaneously, and the distribution of flights over these two routes is addressed in parallel. Then, a new version of the so-called MOEA/D optimization algorithm is developed to solve the formulated optimization problem. Two different case studies, one at Rotterdam The Hague Airport and one at Amsterdam Airport Schiphol in The Netherlands, are carried out to evaluate the reliability and applicability of the proposed approach. The obtained results reveal that the proposed approach can provide solutions which can balance more effectively the concerned metrics such as the number of annoyed people, fuel burn, number of people exposed to certain noise levels, and number of aircraft movements which people are subjected to. [ABSTRACT FROM AUTHOR]

Abstract: Background: Both the WHO and the EC recommend the use of L night as the primary indicator for sleep disturbance. Still, a key question for noise policy is whether the prediction of sleep quality could be improved by taking the number of events into account in addition to L night. Objectives: The current paper investigates the association between sleep quality and the number of aircraft noise events. The first aim of this study was to investigate whether, for the purpose of predicting sleep quality measured by motility, the nummer of events is adequately represented in L night for the purpose of predicting sleep quality measured by motility. The second aim was to investigate whether the number of events at a given L night has an additional predictive value. In addition, it was explored whether the total number of events should be taken into account for the production of sleep quality, or only the number of events exceeding a certain sound pressure level. Methods: This study is based on data of a field study among 418 people living within a range of 20km from Amsterdam Airport Schiphol. The data from this study are well suited for this purpose, since for every subject both the number and the exposure level of events are available. Sleep quality was measured by motility, derived from actimeters worn on the wrist, and by self-reported sleep quality scored on a 11-point scale. Mixed linear regression models were built in a stepwise manner to predict sleep quality during a sleep period time. Results: The results show that, given a certain equivalent noise level, additional information on the overall number of events does not improve the prediction of sleep quality. However, the number of events above L Amax of 60dB was related to an increase in mean motility, indicating lower sleep quality. No effect of number of events was found on self-reported sleep quality. Conclusions: This study suggests that the number of events is more or less adequately represented in L night and only the number of high noise level events may have additional effects on sleep quality as measured by motility. This may be viewed as an indication that, in addition to L night, the number of events with a relatively high L Amax could be used as a basis for protection against noise-induced sleep disturbance. [Copyright &y& Elsevier]

Abstract: Noise monitoring continues to be one of the most important tools in noise management around airports, since noise pollution is a serious problem for the surrounding communities. The monitoring units must be reliable and precise in order to ensure the quality of the results provided. As a previous step to achieve this, it is necessary to make an estimation of the uncertainty of the results, taking into account the contribution of every single element in the measurement chain. Among other contributions to uncertainty as listed in ISO 20906, the events marking system has an influence on the measurement results on two different levels: the first one, derives from the human factors affecting the event detection while the second one derives from the error rates of the classification–identification chain. In this paper, the focus is set on the latter, which has been called identification uncertainty. A model has been defined for its estimation and a methodology of application has been described. The results have been calculated for some specific situations in order to clarify the methodology and to have some estimations of the value of this contribution to uncertainty. Just for a location very close to the airport (aircraft events range over 20dB), this contribution to uncertainty can be up to 0.5dB when simple detection techniques are used, and can be reduced to approximately 0.1dB when radar tracking is used to enhance the identification task. In more complex acoustic environments, the identification uncertainty can increase up to 5dB (or more) in the absence of accurate classification/identification tools. [Copyright &y& Elsevier]

Noise exposure can affect sleep, health and cognitive performance, and it disproportionately affects communities of color. This study has the objective of evaluating both conventional and supplemental noise metrics in a community noise survey examining Southwest Detroit, Michigan, a densely populated and industrialized area with extensive truck traffic on residential streets. Sound pressure level (SPL) monitors were deployed at 21 residential sites within 900 m of a major interstate highway. With assistance from youth volunteers, continuous SPL measurements were obtained for 1.5–7 days at each site, and short-term vehicle counts on local roads were recorded. We calculated conventional noise metrics, including the day-evening-night average sound level L DEN and the 90th percentile 1-hr maximum L 10 (h), and evaluated the effect of distance from highways, traffic volume, time-of-day, and other factors. Supplemental metrics potentially appropriate for intermittent traffic noise were calculated, including fraction of time over specific SPL thresholds using a new metric called F DEN , which is the fraction of time over 60, 65 and 70 dB during night, evening and daytime periods, respectively, and a peak noise metric called L 2P (h), which utilizes the 98th percentile SPL within time blocks to increase robustness. The conventional metrics indicated five sites that exceeded 70 dB, and the highest noise levels were found within ~50 m of truck routes, arterials and freeway ramps. The estimated impact of truck traffic ranged up to 17 dB for hourly averages and to 33 dB for 1-s peaks. The conventional metrics did not always capture short-term noise exposures, which may be especially important to annoyance and sleep issues. In addition to showing widespread exposure to traffic noise in the study community that warrants consideration of noise abatement strategies, the study demonstrates the benefits of supplemental noise metrics and community engagement in noise assessment. • A community noise survey was conducted in Detroit, Michigan at 21 residential sites. • Community members and youth assisted in making noise and traffic measurements. • Noise near truck routes, arterials and freeway ramps exceeded guideline levels. • Conventional noise metrics were supplemented with metrics for short-term noise exposure. • Traffic noise was widespread and noise abatement strategies should be considered. [ABSTRACT FROM AUTHOR]

In addition to air pollution, environmental noise has become one of the major hazards for citizens, being Road Traffic Noise (RTN) as its main source in urban areas. Recently, low-cost Wireless Acoustic Sensor Networks (WASNs) have become an alternative to traditional strategic noise mapping in cities. In order to monitor RTN solely, WASN-based approaches should automatize the off-line removal of those events unrelated to regular road traffic (e.g., sirens, airplanes, trams, etc.). Within the LIFE DYNAMAP project, 15 urban Anomalous Noise Events (ANEs) were described through an expert-based recording campaign. However, that work only focused on the overall analysis of the events gathered during non-sequential diurnal periods. As a step forward to characterize the temporal and local particularities of urban ANEs in real acoustic environments, this work analyses their distribution between day (06:00–22:00) and night (22:00–06:00) in narrow (1 lane) and wide (more than 1 lane) streets. The study is developed on a manually-labelled 151-h acoustic database obtained from the 24-nodes WASN deployed across DYNAMAP's Milan pilot area during a weekday and a weekend day. Results confirm the unbalanced nature of the problem (RTN represents 83.5% of the data), while identifying 26 ANE subcategories mainly derived from pedestrians, animals, transports and industry. Their presence depends more significantly on the time period than on the street type, as most events have been observed in the day-time during the weekday, despite being especially present in narrow streets. Moreover, although ANEs show quite similar median durations regardless of time and location in general terms, they usually present higher median signal-to-noise ratios at night, mainly on the weekend, which becomes especially relevant for the WASN-based computation of equivalent RTN levels. [ABSTRACT FROM AUTHOR]

Human hearing adapts to steady signals, but remains very sensitive to fluctuations as well as to prominent, salient noise events. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these fluctuations, descriptors have been proposed in the literature and, among these, the intermittency ratio (IR) has been formulated to quantify the eventfulness of an exposure from transportation noise. This paper deals with the application of IR to urban road traffic noise data, collected in terms of 1 s A-weighted sound pressure level (SPL), without being attended, monitored continuously for 24 h in 90 sites in the city of Milan. IR was computed on each hourly data of the 251 time series available (lasting 24 h each), including different types of roads, from motorways to local roads with low traffic flow. The obtained hourly IR values have been processed by clustering methods to extract the most significant temporal pattern features of IR in order to figure out a criterion to classify the urban sites taking into account road traffic noise events, which potentially increase annoyance. Two clusters have been obtained and a "non-acoustic" parameter x, determined by combination of the traffic flow rate in three hourly intervals, has allowed to associate each site with the cluster membership. The described methodology could be fruitfully applied on road traffic noise data in other cities. Moreover, to have a more detailed characterization of noise exposure, IR, describing SPL short-term temporal variations, has proved to be a useful supplementary metric accompanying LAeq, which is limited to measure the energy content of the noise exposure. [ABSTRACT FROM AUTHOR]