Improving strategic noise mapping of railway noise in Europe: Refining CNOSSOS-EU calculations using TWINS.

The Environmental Noise Directive (2002/49/EC) requires all European Union Member States to produce strategic noise maps using a common assessment methodology: CNOSSOS-EU. The reliability of CNOSSOS-EU railway noise evaluation is dependent on the input vehicle and track transfer functions. The CNOSSOS-EU default database contains the currently available choices for these transfer functions. However, these available transfer functions are limited and of insufficient quality, resulting in large errors in noise level calculations. An approach is presented, introducing an established analytical railway rolling noise calculation technique (TWINS), to extract more reliable and specific transfer functions. A case study consisting of railway rolling noise mitigation measures is defined and used as the basis for extracting and testing these transfer functions. The extracted transfer functions reduce the average deviation between CNOSSOS-EU and reference calculations using TWINS from 6.1 dB(A) to 0.8 dB(A) in absolute sound power levels, and from 1.2 db(A) to 0.3 dB(A) in estimates of noise reduction potential for the defined mitigation measures. Application of this approach shows potential to improve the quality and depth of the existing CNOSSOS-EU default database. This may lead to more reliable estimations of railway noise in the strategic noise maps and the subsequent assessment of its harmful effects.

Impacts of changes in environmental exposures and health behaviours due to the COVID-19 pandemic on cardiovascular and mental health: A comparison of Barcelona, Vienna, and Stockholm.

Responses to COVID-19 altered environmental exposures and health behaviours associated with non-communicable diseases. We aimed to (1) quantify changes in nitrogen dioxide (NO2), noise, physical activity, and greenspace visits associated with COVID-19 policies in the spring of 2020 in Barcelona (Spain), Vienna (Austria), and Stockholm (Sweden), and (2) estimated the number of additional and prevented diagnoses of myocardial infarction (MI), stroke, depression, and anxiety based on these changes. We calculated differences in NO2, noise, physical activity, and greenspace visits between pre-pandemic (baseline) and pandemic (counterfactual) levels. With two counterfactual scenarios, we distinguished between Acute Period (March 15th - April 26th, 2020) and Deconfinement Period (May 2nd - June 30th, 2020) assuming counterfactual scenarios were extended for 12 months. Relative risks for each exposure difference were estimated with exposure-risk functions. In the Acute Period, reductions in NO2 (range of change from -16.9 µg/m3 to -1.1 µg/m3), noise (from -5 dB(A) to -2 dB(A)), physical activity (from -659 MET*min/wk to -183 MET*min/wk) and greenspace visits (from -20.2 h/m to 1.1 h/m) were largest in Barcelona and smallest in Stockholm. In the Deconfinement Period, NO2 (from -13.9 µg/m3 to -3.1 µg/m3), noise (from -3 dB(A) to -1 dB(A)), and physical activity levels (from -524 MET*min/wk to -83 MET*min/wk) remained below pre-pandemic levels in all cities. Greatest impacts were caused by physical activity reductions. If physical activity levels in Barcelona remained at Acute Period levels, increases in annual diagnoses for MI (mean: 572 (95% CI: 224, 943)), stroke (585 (6, 1156)), depression (7903 (5202, 10,936)), and anxiety (16,677 (926, 27,002)) would be anticipated. To decrease cardiovascular and mental health impacts, reductions in NO2 and noise from the first COVID-19 surge should be sustained, but without reducing physical activity. Focusing on cities' connectivity that promotes active transportation and reduces motor vehicle use assists in achieving this goal.

Noise measurements as a proxy to evaluating the response to recommendations in times of crisis: An update analysis of the transition to the second wave of the CoViD-19 pandemic in Central Stockholm, Sweden.

Sweden stands out among the other European countries by the degree of restrictive measures taken towards handling the 2019 coronavirus outbreak, associated with the CoViD-19 pandemic. While several governments have imposed a nationwide total or partial lockdown to slow down the spread of the virus, the Swedish government has opted for a recommendation-based approach together with a few imposed restrictions. In a previous contribution by the authors, the impact of the Swedish strategy was observed through the monitored variation of the city noise levels during a period associated with the so-called "first wave" of the pandemic in Stockholm. A very strong impact of these recommendations was shown on the evolution of the noise levels in central Stockholm. This highlighted the potential of acoustic sensor networks both for enforcement of regulation and monitoring of the effectiveness of their implementation. The present contribution presents a follow-up to this urban noise monitoring in central Stockholm, Sweden, for the period leading to the so-called "second wave" of the pandemic in Europe. Both the evolution of adherence to the recommendations and the impact of the recurrence of cases combined with reinforced recommendations are observed through the evolution of the measured noise levels. While the measurements show a gradual lower level of compliance, in particular, past the summer break, these also show again a rapid response to the reinforced recommendations issued by the authorities in mid-fall of 2020. These observations thus confirm the potential associated with detailed urban noise monitoring, for instance here acting as a proxy to evaluating the response to recommendations or restrictions in times of crisis.

An observation of the impact of CoViD-19 recommendation measures monitored through urban noise levels in central Stockholm, Sweden.

Sweden stands out among the other European countries by the degree of restrictive measures taken towards handling the 2019 coronavirus outbreak, associated with the CoViD-19 pandemic. While several governments have imposed a nationwide total or partial lockdown in order to slow down the spread of the virus, the Swedish government has opted for a recommendation-based approach together with a few imposed restrictions. In the present contribution, the impact of this strategy will be observed through the monitored variation of the city noise levels during the associated period. The data used are recorded during a campaign of over a full year of noise level measurements at a building façade situated in a busy urban intersection in central Stockholm, Sweden. The noise level reductions, observed during the period of restrictions, are shown to be comparable to those found for the two most popular public holidays in Sweden with a peak reduction occurring during the first half of April 2020. Contrary to what has been recently discussed in public media, the spread of the virus, the recommendations, and the restrictions imposed during the ongoing pandemic clearly have had a significant effect on the transport and other human-related activities in Stockholm. In this unique investigation, the use of distributed acoustic sensors has thus shown to be a viable solution not only to enforce regulations but also to monitor the effectiveness of their implementation.

A residue-based mode selection and sorting procedure for efficient poroelastic modeling in acoustic finite element applications.

Analysis of three-dimensional sound propagation in porous elastic media with the Finite Element (FE) method is, in general, computationally costly. Although it is the most commonly used predictive tool in complex noise control applications, efficient FE solution strategies for large-size industrial problems are still lacking. In this work, an original procedure is proposed for the sorting and selection of the modes in the solution for the sound field in homogeneous porous domains. This procedure, validated on several 2D and 3D problems, enables to reduce the modal basis in the porous medium to its most physically significant components. It is shown that the size of the numerical problem can be reduced, together with matrix sparsity improvements, which lead to the reduction in computational time and enhancements in the efficacy of the acoustic response computation. The potential of this method for other industrial-based noise control problems is also discussed.

A modal-based reduction method for sound absorbing porous materials in poro-acoustic finite element models.

Structural-acoustic finite element models including three-dimensional (3D) modeling of porous media are generally computationally costly. While being the most commonly used predictive tool in the context of noise reduction applications, efficient solution strategies are required. In this work, an original modal reduction technique, involving real-valued modes computed from a classical eigenvalue solver is proposed to reduce the size of the problem associated with the porous media. In the form presented in this contribution, the method is suited for homogeneous porous layers. It is validated on a 1D poro-acoustic academic problem and tested for its performance on a 3D application, using a subdomain decomposition strategy. The performance of the proposed method is estimated in terms of degrees of freedom downsizing, computational time enhancement, as well as matrix sparsity of the reduced system.