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The different measures taken by the competent authorities to tackle the effects of the COVID-19 pandemic affected the acoustic environment worldwide, resulting in significant reductions of noise levels. However, most of the investigations mainly focused on the lockdown during spring 2020, in which all non-essential industrial and commercial activities were prohibited, being people requested to stay at home. The analysis of the data collected and processed by the wireless acoustic sensor network deployed in Milan, Italy, by the DYNAMAP project showed a significant drop of sound levels, mainly due to road traffic as well as other noise sources, denoted as anomalous noise events (ANEs). This work extends that research through a long-term global analysis of the COVID-19 pandemic effects from January 2020 to August 2021, including data clustering to identify local patterns of the sound environment of Milan. As a result of the first hard and subsequent second soft lockdown imposed by the Italian authorities, a double V-shape reduction pattern of the mean sound levels Lden (with and without ANEs) is observed, with maximum drops of around 6 dB and 3 dB, respectively, surrounded with similar progressive reductions in both pre- and post-lockdown periods, showing statistically significant differences. A complementary pattern is obtained regarding the detection of ANEs. The clustering of Lden indicators yields three different sound patterns in the second lockdown, both in terms of noise levels and ANEs, depending on sensor locations and traffic flow variations, unlike the first lockdown with a homogeneous behaviour throughout the city.

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices' values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs. Thus, there is a need to reduce these biases and incongruences to ensure an accurate analysis and comparison between soundscape ecology studies and habitat assessments. In this study, we propose and validate an audio recording equalization protocol to reduce eco-acoustic indices' biases, by testing three soundscape recorder models: Song Meter Micro, Soundscape Explorer Terrestrial and Audiomoth. The equalization process aligns the signal amplitude and frequency response of the soundscape recorders to those of a type 1 level meter. The adjustment was made in MATLAB R2023a using a filter curve generated comparing a reference signal (white noise); the measurements were performed in an anechoic chamber using 11 audio sensors and a type 1 sound level meter (able to produce a .WAV file). The statistical validation of the procedure was performed on recordings obtained in an urban and Regional Park (Italy) assessing a significant reduction in indices' biases on the Song Meter Micro and Audiomoth.

Passive acoustic monitoring (PAM) is widely used by soundscape and bioacoustics researchers. Nowadays, there is a large number of instruments available to record environmental sound, with different characteristics and costs. Given this availability, using all the devices on hand, even from different manufacturers, can be tempting since it allows to expand the area of study with less costs. Unfortunately, due to their diverse frequency response, this procedure introduces biases in a comparative analysis of the recordings (e.g., the computation of acoustic parameters and indices, and the following elaborations). For these reasons, equalization of audio recording is fundamental to ensure proper analysis. Therefore, in this study, we evaluated the effects of the equalization on the data acquired by two soundscape recorder typologies (Song-Meter-Micro and Soundscape-Explorer-Terrestrial). The evaluation was carried out by computing the eco-acoustic indices. The equalization was performed in a laboratory: the soundscape recorders and a class 1 sound level meter (able to produce a.WAV file) were exposed to a white noise source. The equalization curve was calculated in MATLAB environment with a successful response. As a second step, its effect on the eco-acoustic indices was evaluated by applying it to audio recordings from a park in Milan (Italy).

Predicting the sound quality of an environment represents an important task especially in urban parks where the coexistence of sources of anthropic and biophonic nature produces complex sound patterns. To this end, an index has been defined by us, denoted as soundscape ranking index (SRI), which assigns a positive weight to natural sounds (biophony) and a negative one to anthropogenic sounds. A numerical strategy to optimize the weight values has been implemented by training two machine learning algorithms, the random forest (RF) and the perceptron (PPN), over an augmented data-set. Due to the availability of a relatively small fraction of labelled recorded sounds, we employed Monte Carlo simulations to mimic the distribution of the original data-set while keeping the original balance among the classes. The results show an increase in the classification performance. We discuss the issues that special care needs to be addressed when the augmented data are based on a too small original data-set.

The goal of estimating a soundscape index, aimed at evaluating the contribution of the environmental sound components, is to provide an accurate “acoustic quality” assessment of a complex habitat. Such an index can prove to be a powerful ecological tool associated with both rapid on-site and remote surveys. The soundscape ranking index (SRI), introduced by us recently, can empirically account for the contribution of different sound sources by assigning a positive weight to natural sounds (biophony) and a negative weight to anthropogenic ones. The optimization of such weights was performed by training four machine learning algorithms (decision tree, DT; random forest, RF; adaptive boosting, AdaBoost; support vector machine, SVM) over a relatively small fraction of a labeled sound recording dataset. The sound recordings were taken at 16 sites distributed over an area of approximately 22 hectares at Parco Nord (Northern Park) of the city Milan (Italy). From the audio recordings, we extracted four different spectral features: two based on ecoacoustic indices and the other two based on mel-frequency cepstral coefficients (MFCCs). The labeling was focused on the identification of sounds belonging to biophonies and anthropophonies. This preliminary approach revealed that two classification models, DT and AdaBoost, trained by using 84 extracted features from each recording, are able to provide a set of weights characterized by a rather good classification performance (F1-score = 0.70, 0.71). The present results are in quantitative agreement with a self-consistent estimation of the mean SRI values at each site that was recently obtained by us using a different statistical approach.

We have performed a detailed analysis of the soundscape inside an urban park (located in the city of Milan) based on simultaneous sound recordings at 16 locations within the park. The sound sensors were deployed over a regular grid covering an area of about 22 hectares, surrounded by a variety of anthropophonic sources. The recordings span 3.5 h each over a period of four consecutive days. We aimed at determining a soundscape ranking index (SRI) evaluated at each site in the grid by introducing 4 unknown parameters. To this end, a careful aural survey from a single day was performed in order to identify the presence of 19 predefined sound categories within a minute, every 3 minutes of recording. It is found that all SRI values fluctuate considerably within the 70 time intervals considered. The corresponding histograms were used to define a dissimilarity function for each pair of sites. Dissimilarity was found to increase significantly with the inter-site distance in space. Optimal values of the 4 parameters were obtained by minimizing the standard deviation of the data, consistent with a fifth parameter describing the variation of dissimilarity with distance. As a result, we classify the sites into three main categories: "poor", "medium" and "good" environmental sound quality. This study can be useful to assess the quality of a soundscape in general situations.

The-growing influence of urbanisation on green areas can greatly benefit from passive acoustic monitoring (PAM) across spatiotemporal continua to provide biodiversity estimation and useful information for conservation planning and development decisions. The capability of ecoacoustic indices to capture different sound features has been harnessed to identify areas within the Parco Nord of Milan, Italy, characterised by different degrees of anthropic disturbance and biophonic activity. For this purpose, we used a network of very low-cost sensors distributed over an area of approximately 20 hectares to highlight areas with different acoustic properties. The audio files analysed in this study were recorded at 16 sites on four sessions during the period 25–29 May (2015), from 06:30 a.m. to 10:00 a.m. Seven eco-acoustic indices, namely Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-Acoustic Index (BI), Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NSDI), and Dynamic Spectral Centroid (DSC) were computed at 1 s integration time and the resulting time series were described by seven statistical descriptors. A dimensionality reduction of the indices carrying similar sound information was obtained by performing principal component analysis (PCA). Over the retained dimensions, describing a large (∼80%) variance of the original variables, a cluster analysis allowed discriminating among sites characterized by different combination of eco-acoustic indices (dimensions). The results show that the obtained groups are well correlated with the results of an aural survey aimed at determining the sound components at the sixteen sites (biophonies, technophonies, and geophonies). This outcome highlights the capability of this analysis of discriminating sites with different environmental sounds, thus allowing to create a map of the acoustic environment over an extended area.

Considering the actual “vertical” housing development in the last few decades, the number of people living in high-rise building is continuously increasing. At present in the city of Milanmore than 500 (0.4% of total) buildings exceed the height of 50 m, with a number of residents of about 14000 (1% of total). For this reason, we planned an experimental campaign to study the vertical noise profile through air-balloon measurements in the city of Milan. Results show that the noise levels increase with the height with respect to ground-reference measurements, as a result of the contribution from an extended area. The highest levels are reached at about 90 m. Critical issues regarding this measurement technique are also outlined.

The aim of this paper is to propose the use of passive acoustic monitoring (PAM) as a noninvasive method to investigate the state of communities and ecosystems. PAM operates through the study and characterization of the soundscape of an area. One of the three components of the soundscape (beside geophony and biophony) is anthrophony, which is the collection of sounds produced by human activities. This kind of sounds can have effects on natural environments and natural population. In this study, recording instruments and sampling techniques have been used to acquire and collect sound data for long periods (two weeks) in a natural terrestrial ecosystem (Ticino Park) which is affected by road and rail traffic noise. The analysis conducted studied the trends of the eco-acoustic indices belonging to three measurement sites to detect the presence of characteristic trends and to evaluate the influence of the two anthropogenic noise sources at different distances.

Green areas suffer the growing influence of urbanization and may benefit from the use of passive acoustic monitoring (PAM) which can provide biodiversity estimation and conservation especially in fragile environments such as urban parks and protected areas. A network of low-cost sensors has been distributed over an area of approximately 20 hectares at the Parco Nord of Milan, Italy, to highlight areas with different acoustic characteristics. The audio files analysed in this study were recorded at 16 sites on four sessions between May 25th and May 29th 2015 from 06:30 a.m. to 10:00 a.m.. Seven eco-acoustic indices have been computed and analysed. A map of eco-acoustic indices has been built and validated by comparing the results with an aural survey aimed at determining the sound components at each of the sixteen sites (biophonies, technophonies and geophonies). This approach may represent a useful tool for an integrated approach aimed at conservation planning and development decisions.

We applied standard acoustic methods to record, analyze and compare anthropogenic and biological signals belonging to the soundscape of artificial marine habitats. The study was conducted on two tanks located at the Acquario di Genova (Italy), the “Red Sea” and the “Tropical Lagoon” tanks, which represent different living environments hosting a variety of species and background sounds. The use of seven eco-acoustic indices, whose time series spanned the entire period of study, allowed the characterization of the environments. We investigated the extent to which eco-acoustic indices might describe the soundscape in an artificial marine environment surrounded by a background of mechanical noise, overlapping the diurnal/nocturnal fish chorusing produced by soniferous species. Three specific types of sounds emerged: (1) mechanical ones produced by the life-support system of the tanks; (2) anthropic origin ones due to maintenance and introduction of food; and (3) temporal trends associated with day/night cycles, especially impacted by artificial lighting. We searched for selected spectral patterns that were correlated to the time series of the eco-acoustic indices. The observed activity was found to be consistent with the sound emission of three specific fish species hosted in the tanks. The power spectral density (PSD) confirmed the presence of correlated signals (at 95th and 99th percentiles) for the identified frequency intervals. We expect that this method could be useful for studying the behavior of aquatic animals without intruding into their habitats.

We investigate the possible presence of ‘long time’ memory in the auto-correlations of biophonic activity of environment sound. The study is based on recordings taken at two sites located in the Parco Nord of Milan (Italy), characterized by a wooded land, rich in biodiversity and exposed to different sources and degrees of anthropogenic disturbances. The audio files correspond to a three-day recording campaign (1-min recording followed by 5-min pause), from (17:00) April 30 to (17:00) May 3, 2019, which have been transformed into ecoacoustic indices time series. The following eight indices have been computed: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-acoustic Index (BI), Acoustic Entropy Index (H), Acoustic Richness index (AR), Normalized Difference Soundscape Index (NSDI) and Dynamic Spectral Centroid (DSC). We have grouped the indices carrying similar sound information by performing a principal component analysis (PCA). This allows us to reduce the number of variables from eight to three by retaining a large (≳80%) variance of the original variables. The time series corresponding to the reduced set of new variables have been analyzed, and both seasonal and possible long term trend components have been extracted. We find that no trends are present, i.e. the resulting time series are stationary, and the auto-correlations of the three selected PCA dimensions and associated residuals (obtained after extracting the seasonal components) can be determined. The calculations reveal the presence of a “memory” of few (≲5) hours long in the environment sound, for the two sites considered, which is quantified by the Hurst exponent, H. For Site 1, we find an overall effective Hurst exponent, Hdim≃0.88, for all three dimensions, and Hres≃0.75 for the residuals. For Site 2, the exponents are slightly smaller, amounting to 0.80 and 0.60, respectively. We attempt to correlate the Hurst exponents with a quality index obtained

Over the last century, anthropogenic activities have caused significant changes in soundscapes. These alterations are mainly caused by growing noise related to the expansion of cities and their connections (e.g. roads). It is urgent to understand the distribution of noise pollution and its effect on biodiversity, especially in large cities, aiming to propose legal regulations and mitigation actions to reduce its impact. In this study, we assessed the soundscape of the pocket- park Vivaio-Bicocca of Milan (Italy), in a highly anthropized urban context, as a starting point to understand the effect of noise pollution on the city wildlife. Audio recordings took place 24h a day from May 31st to June 14th 2022 (1 minute of recordings followed by 5-minutes pause) with autonomous recorders in three sites 45m apart, while noise level was measured using a Sound-Level-Meter. Soundscape analyses were performed calculating eco- acoustic indices (e.g. Acoustic Complexity Index, Acoustic Diversity Index, Normalized Difference Soundscape Index) in the R environment. As expected, the soundscape of the three sites resulted quite similar, composed of biophony and a high quantity of anthropophony. We hypothesize that the central site could be representative of the whole park and be used on its own for the soundscape characterization.

Noise annoyance depends not only on sound energy, but also on other features, such as those in its spectrum (e.g., low frequency and/or tonal components), and, over time, amplitude fluctuations, such as those observed in road, rail, or aircraft noise passages. The larger these fluctuationsthe more annoying a sound is generally perceived. Many algorithms have been implemented to quantify these fluctuations and identify noise events, either by looking at transients in the sound level time history, such as exceedances above a fixed or time adaptive threshold, or focusing on the hearing perception process of such events. In this paper, four criteria to detect sound were applied to the acoustic monitoring data collected in two urban areas, namely Andorra la Vella, Principality of Andorra, and Milan, Italy. At each site, the 1 s A-weighted short LAeq,1s time history, 10 min long, was available for each hour from 8:00 a.m. to 7:00 p.m. The resulting 92-time histories cover a reasonable range of urban environmental noise time patterns. The considered criteria to detect noise events are based on: (i) noise levels exceeding by +3 dB the continuous equivalent level LAeqT referred to the measurement time (T), criteria used in the definition of the Intermittency Ratio (IR) to detect noise events; (ii) noise levels exceeding by +3 dB the running continuous equivalent noise level; (iii) noise levels exceeding by +10 dB the 50th noise level percentile; (iv) progressive positive increments of noise levels greater than 10 dB from the event start time. Algorithms (iii) and (iv) appear suitable for notice-event detection; that is, those that (for their features) are clearly perceived and potentially annoy exposed people. The noise events detected by the above four algorithms were also evaluated by the available anomalous noise event detection (ANED) procedure to classify them as produced by road traffic noise or something else. Moreover, the assessment of the sonic environment by the H

In this paper, we present the results of the noise monitoring in the urban area of Milan, Italy, associated with COVID-19 outbreak. In order to limit the diffusion of the pandemic, Italy adopted growing levels of restrictive measures, which ended with a 41-day lockdown from March 23 to May 3 2020. This action created a new kind of environment including a remarkable reduction of air, water and soil pollutants, together with a partial recovery of the ecosystems otherwise compromised. The presence of a permanent noise monitoring system made of 24 sensors installed in the city of Milan, allowed capturing the changes in the urban sound environment in a pre, during and post-lockdown period (months from February to June 2020). The comparison of the noise levels in terms of both absolute noise levels (Lden) and hourly noise profiles (median over lockdown period) with the same period of 2019, showed a dramatic reduction of the noise levels of approximately 6 dB. Splitting the contribution of all-non-traffic noises or anomalous noise events (ANE) from the recorded noise levels, we observe a greater contribution of the latter during the lockdown period. The use of DYNAMAP noise prediction system over an extended urban area allowed the evaluation of the population exposure to noise, estimating an increase of 14.9% and 16.4% of the exposed population to noises with Lden below 53 dB(A) and Lnight below 45 dB(A) with respect to 2019.

We investigated the statistical properties of the sounds recorded at a site located in the Parco Nord of Milan, Italy, characterized by wooded land rich in biodiversity and exposed to different sources and types of anthropogenic disturbances with the aim of deriving information on its environmental quality in terms of biophonic presence and athropic disturbance. A time series of eco-acosutic indices were determined for 616 audio files recorded from 30 April 2019 (5:00 p.m.) to 3 May 2019 (5:00 a.m.) with a 1-min duration followed by a 5-min pause (10 recordings per hour). In the present study, the following indices were computed: the Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-acoustic Index (BI), Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NSDI) and Dynamic Spectral Centroid (DSC). Cluster analysis performed on the corresponding time series yielded a dimensional reduction from seven down to three. The results show a clear separation of the eco-acoustic indices into two clusters, reflecting the different dynamics and diversity behaviour throughout the recordings. A post-processing aural survey was also performed, aiming at determining biophonic activities (mainly avian vocalization and other animals), the characteristics of technophonies sources (mainly road traffic noise and airplane fly-overs), human presence (voices and steps) and geophonies (rain and wind). The statistical analysis proved to be a robust tool due to the good matching obtained with the aural survey outcomes. The overall quality of the Parco Nord phonic activity was found to be low. Notwithstanding the presence of avian species, highlighted by the characteristic dawn chorus, both clusters revealed low “scores” of NDSI and DSC indices heavily influenced by road traffic sources. This study represents the first step toward the realization of maps of eco-acoustic indices for the long-term monitoring of fragile habitats.

No robust evidence is provided by literature regarding the management of intracranial hypertension following severe traumatic brain injury (TBI). This is mostly due to the lack of prospective randomized controlled trials (RCTs), the presence of studies containing extreme heterogeneously collected populations and controversial considerations about chosen outcome. A scientific society should provide guidelines for care management and scientific support for those areas for which evidence-based medicine has not been identified. However, RCTs in severe TBI have failed to establish intervention effectiveness, arising the need to make greater use of tools such as Consensus Conferences between experts, which have the advantage of providing recommendations based on experience, on the analysis of updated literature data and on the direct comparison of different logistic realities. The Italian scientific societies should provide guidelines following the national laws ruling the best medical practice. However, many limitations do not allow the collection of data supporting high levels of evidence for intracranial pressure (ICP) monitoring and decompressive craniectomy (DC) in patients with severe TBI. This intersociety document proposes best practice guidelines for this subsetting of patients to be adopted on a national Italian level, along with joint statements from “TBI Section” of the Italian Society of Neurosurgery (SINch) endorsed by the Neuroanesthesia and Neurocritical Care Study Group of the Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI). Presented here is a recap of recommendations on management of ICP and DC supported a high level of available evidence and rate of agreement expressed by the assemblies during the more recent consensus conferences, where members of both groups have had a role of active participants and supporters. The listed recommendations have been sent to a panel of experts consisting of the 107 members of the “T

Noise produces a direct negative influence on the physical and psychological well-being of the exposed population. Surveys addressed to the population allow to evaluate the degree of annoyance produced on the population by different urban noise sources. In this paper, we analyze the results of surveys distributed to people living or working in District 9 of Milan. We have chosen this area because of the presence of permanent noise monitoring stations installed as part of DYNAMAP project. DYNAMAP is a European Life project realized with the aim of developing a dynamic approach to noise mapping, owing to its capability to update environmental noise levels through a direct link with a limited number of noise monitoring sensors, permanently installed in the area. Here, we present the correlation between the population perception to annoying noises (derived from the answers provided to the surveys) and the energetic and statistical acoustic indices (derived from the elaboration of the acoustic data collected by using the DYNAMAP sensors) in order to have a more realistic evaluation of the soundscape in urbanized areas.

A noise monitoring campaign has been performed in an urban park of Milan (Italy) called Parco Nord. The area of study is a large peri-urban park in the northern part of the city, characterized by wooded land rich in biodiversity and exposed to different sources and degrees of anthropogenic disturbances, such as road traffic noise and artificial light. The acoustic environment is rather complex due to the contemporary presence of different noise sources, leading to the difficult task of discriminating them in audio data. Due to these multifactorial characteristics, we evaluated different eco-acoustic indices in the attempt to derive a methodology to evaluate the potential of sound ecology indicators to discriminate the different types of sounds present in medium-large urban parks. Two different sites have been considered with different degree of anthropogenic disturbance. Time series of about two-week recordings have been transformed into eco-acoustics indices and statistically analysed. The results show a redistribution of recordings into two clusters associated with different sound components and different periods of the day. This allowed the identification of different degrees of biophonic and/or anthropogenic activities throughout the day in the two sites.

Annoying sounds are very common in urban areas and can produce negative effects on the human health. An important tool to evaluate the degree of annoyance produced on the population by different noise sources, is represented by surveys directly addressed to the population. In this paper, we analyze the results of surveys distributed to people living or working in 14 areas in District 9 of Milan. In these areas, low-cost permanent noise monitoring stations have been installed as part of DYNAMAP project. DYNAMAP is a European Life project aiming at developing a real-time acoustic mapping system on a pilot area by means of a limited number of monitoring stations. The results obtained from the surveys have been analyzed, in order to correlate the human perception of different noise sources or characteristics of the urban soundscape. This to better discriminate the degree of annoyance due to anthropogenic noise sources perceived by the population of an urbanized area, such as that of District 9 of Milan.

An acoustics survey has been performed at Genova (Italy) Aquarium aiming at characterizing the acoustic environment of tropical underwater habitats. Mid-term (5-7 days) measurements in tank containing tropical habitats have been chosen for a preliminary analysis. Spectral analyzes and eco-acoustic indices have been applied to derive information on the marine population activity and other sources. The measurements are strongly influenced by the presence of background noise, especially due to the technological systems dedicated to the operation of the aquarium which could not be completely silenced. However, the use of different indicators allowed to describe an artificial environment characterized by a strong anthropic influence and highlighted the ability of some indicators to bring out the presence of biological activity. Such approach will be used to compare environments with different degree of disturbance and derive information on the environmental quality of both artificial and natural habitats.

DYNAMAP, a European Life project, provides a real-time image of the noise generated by vehicular traffic in urban and suburban areas, developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. Traffic noise data within a urban pilot area (Area 9 of Milan), collected by 24 monitoring sensors, are used to build-up a "real time" noise map. DYNAMAP is based on a statistical approach implying that information captured by each sensor must be representative of an extended area, and simultaneously uncorrelated from that of other stations. The study of the correlations among the sensors represents a further contribution in refining the sampling network design.

The paper describes the analysis of noise annoyance complaints submitted by citizens to the Municipality of Milan, Italy, from years 2000 to 2015. These complaints have been organized in a database and analysed according to: i) types of noise sources (technical facilities, music, transport infrastructures, etc.), ii) activities (retail and catering businesses, production, service sector, etc.) and iii) outcomes of the complaints inspection by local authorities. In addition, by means of a Geographic Information System (GIS) software, the spatial distribution of complaints has been determined according to the noise source type and activities, including also a geo-statistical representation by complaints density maps. The results show that, despite the dominant noise source in urban areas is mainly the road traffic, the other noises, such as those from industrial facilities, constructions and social activities (parties, fairs and open air markets, residential noise, etc.), are perceived as more disturbing. Since 2007, the number of noise complaints (about 100-150 complaints/year) is almost constant across the years. However, these complaints are expected to increase due to the growing and spreading of leisure activities, malls, exhibition centres and event venues, observed for the years 2014-2015.

This Special Issue is focused on all the technologies necessary for the development of an efficient wireless acoustic sensor network, from the first stages of its design to the tests conducted during deployment; its final performance; and possible subsequent implications for authorities in terms of the definition of policies. This Special Issue collects the contributions of several LIFE and H2020 projects aimed at the design and implementation of intelligent acoustic sensor networks, with a focus on the publication of good practices for the design and deployment of intelligent networks in any locations.

The European Life project, called DYNAMAP, has been devoted to provide a real image of the noise generated by vehicular traffic in urban and suburban areas, developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. In the urban area of Milan, the system has been implemented over the pilot area named Area 9. Traffic noise data, collected by the monitoring stations, each one representative of a number of roads with similar characteristics (e.g. daily traffic flow), are used to build-up a “real time” noise map. DYNAMAP has a statistical structure and this implies that information captured by each sensor must be representative of an extended area, thus uncorrelated from other stations. The study of the correlations among the sensors represents a key-point in designing the monitoring network. Another important aspect regards the “contemporaneity” of noise fluctuations predicted by DYNAMAP with those effectively measured at an arbitrary location. Integration times heavily affect the result, with correlation coefficients up to 0.8-0.9 for updating times of 1h. Higher correlations are observed when averaging over groups of roads with similar traffic flow characteristics.

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.

DYNAMAP, a European Life project, aims at giving a real image of the noise generated by vehicular traffic in urban areas developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. The system has been implemented in two pilot areas located in the agglomeration of Milan (Italy) and along the Motorway A90 (Rome-Italy). The paper reports the final assessment of the system installed in the pilot area of Milan. Traffic noise data collected by the monitoring stations, each one representative of a number of roads (groups) sharing similar characteristics (e.g., daily traffic flow), are used to build-up a “real-time” noise map. In particular, we focused on the results of the testing campaign (21 sites distributed over the pilot area and 24 h duration of each recording). It allowed evaluating the accuracy and reliability of the system by comparing the predicted noise level of DYNAMAP with field measurements in randomly selected sites. To this end, a statistical analysis has been implemented to determine the error associated with such prediction, and to optimize the system by developing a correction procedure aimed at keeping the error below some acceptable threshold. The steps and the results of this procedure are given in detail. It is shown that it is possible to describe a complex road network on the basis of a statistical approach, complemented by empirical data, within a threshold of 3 dB provided that the traffic flow model achieves a comparable accuracy within each single groups of roads in the network.

The COVID-19 pandemic was confirmed in Italy at the end of January 2020, when the first positive cases for the virus were identified. At the beginning of March, the virus had spread to all Italian regions and on 10 March 2020 the lockdown phase began, limiting the movement of people and prohibiting almost all commercial activities, businesses and non-essential industries. As a result, millions of people were forced to stay at home, causing a drastic drop in traffic volume, which significantly changed the acoustic environment and air quality of cities. On 4 May 2020, the lockdown was partially lifted and activities were progressively reopened. Therefore, traffic gradually started to increase and, consequently, the noise emitted by motor vehicles. This behaviour was confirmed by the data collected by the DYNAMAP system, an automatic platform developed within the LIFE DYNAMAP project, providing real time traffic noise maps in terms of sound pressure levels and impacts at receivers (people and dwellings exposed to noise level bands). In this paper traffic and non-traffic-related noise events in the cities of Rome and Milan from March to May 2020 are analysed and compared to the corresponding values in 2019 to evaluate the effects of the lockdown period.

From March 23rd to May 3rd 2020, Italy underwent a complete lockdown in the attempt to contain the spread of the pandemic due to Covid-19 outbreak. During this period, a new kind of environment has been experienced in all cities, resulting in an abatement of traffic noise levels. Consequently, due to the prohibition of all non-essential activities, traffic noise dynamics changed as well. In this paper, we analyse the data recorded from the permanent noise monitoring network installed in the pilot area of the city of Milan, Italy. The results show how, besides a dramatic reduction of the noise levels (about 6 dB on average), also the noise pattern was profoundly changed. This is particularly important in the framework of DYNAMAP, a statistically based European project able to predict traffic noise over an extended area based on the noise recorded by limited number of monitoring stations. The change of the traffic dynamics, resulting in different noise patterns of the normalized hourly median profiles for each sensor, pose some limitations about the use of such predicting tool during extraordinary situations such as that experienced during a lockdown.

The characterization of environmental quality and the detection of the first sign of environmental stress, with reference to human intrusion, is currently a very important goal to prevent further environmental degradation, and consequently habitat destruction, in order to take appropriate preservation measures. Besides the traditional field observation and satellite remote sensing, geophonic and/or biophonic sounds have been proposed as potential indicators of terrestrial and aquatic settings’ status. In this work, we analyze a series of short audio-recordings taken in urban parks and bushes characterized by the presence of different human-generated-noise and species abundance. This study aims to propose a tool devoted to the investigation of urban and natural environments in a context with different soundscape qualities, such as, for example, those that can be found in urban parks. The analysis shows the ways in which it is possible to distinguish among different habitats by the use of a combination of different acoustic and sound ecology indices.

Noise complaints, expressed by individuals or a group of people, are the outcome of a complex behaviour depending not only on the noise exposure and its evoked annoyance, but also on other factors such as socio-economic ones. Noise annoyance has significant impacts on the quality of life and health of inhabitants, as well as social cohesion. Thus, noise complaints are a very important issue to tackle for national and local policy makers and for all stakeholders involved in planning and management of noise mitigation actions. Within the above framework, the present study describes the analysis of noise complaints submitted by citizens to the municipality of Milan, Italy, from years 2000 to 2015. These complaints have been organized in a database and analyzed considering: i) types of noise source (technical facilities, music, transport infrastructures, etc.); ii) business/leisure activities (retail and catering businesses, production, service sector, etc.) and iii) outcomes of the complaints inspection by local authorities. In addition, by means of a GIS software, the territorial distribution of noise complaints has been determined according to the noise source category and disturbing activity. This analysis includes also a geo-statistical representation by density maps. The results show that, even though road traffic is the dominant noise source in residential and urban areas, the perception of other noises, such as those from industrial facilities, civil construction and social activities (parties, fairs and open air markets, residential noise, etc.), is perceived as more annoying. The results show that since 2007 the number of noise complaints (about 100-150 complaints/year) remains almost constant across the years. However, the spreading of leisure activities, malls, exhibition centers and venues, as observed for the years 2014-2015, would most likely grow them even more. This outcome can assist the local authority in the management of the activities in order to r

Acoustic maps are, generally, calculated according to noise directives that evaluate the noise exposure levels of a population at a reference height of 4 m to provide values that correspond to the first floors of buildings. However, in large cities, the requirements for high-density housing, such as high-rise apartment buildings, make this evaluation incomplete. In this paper, we study noise propagation at different heights in the context of a medium-sized road network, such as that of Milan, Italy. Considering the “vertical housing” development trend for buildings in large cities, evaluation of the exposure of the population to noise at different heights becomes crucial, as residents might be subject to noise annoyances despite their distance from the source. Here, we present the results of noise measurements at three sites at different heights to observe the pattern of the noise profiles. A three-dimensional acoustic simulation reproducing the entire building structure of Milan was developed to estimate the noise levels generated by vehicle traffic sources at different heights. The predicted noise levels were compared with the measured data. In addition, over the entire urban area of Milan, we selected buildings higher than 50 m to analyse the variation of the noise level exposure at different heights. In this way, it could be possible to study this particular behaviour over a large scale. The results of this investigation may help plan and design new high-rise buildings to reduce the exposure of building dwellers to noise.