Beat Schäffer

Previous research has examined the potential of exposure to greenspaces to reduce maladaptive emotion regulation strategies, such as repetitive negative thinking, and to foster connectedness with non-human nature. However, research comparing green and urban built environments often primarily attributes the benefits of greenspace exposure to their positive features, without explicitly addressing road traffic noise as a potential stressor in urban settings. This study investigated how 30-minute walks in forests and urban built environments with varying levels of road traffic noise in Zürich, Switzerland, affect noise annoyance, connectedness with non-human nature and repetitive negative thinking. By accounting for traffic noise, the aim was to isolate the effects of environment (urban built. vs. forest) with minimal confounding. Data from 354 healthy adults were analyzed. Road traffic noise annoyance was generally lower (i) in forests than urban built settings, (ii) in lower road traffic noise than higher road traffic noise settings, and (iii) in areas with longer than in those with shorter relative quiet time. Notably, the robust association between road traffic noise and annoyance was particularly pronounced in forests. In contrast, neither walking in forests nor in environments with lower road traffic noise nor such with longer relative quiet time was associated with a greater reduction in repetitive negative thinking, a stronger increase in nature relatedness or love and care for nature. The results underscore the role of road traffic noise as a significant health-related stressor and support the need for targeted noise mitigation—particularly around urban forests— to preserve their restorative potential. Additionally, the results highlight the relevance of quiet intervals and temporal noise patterns in shaping perceived annoyance, extending beyond average noise measurements. This study has been registered in the ISRCTN registry (ISRCTN48943261). https://www.isrctn.com/ISRCTN48943261 Registered 23.11.2023.

The increasing volume of air traffic has resulted in a rising number of individuals exposed to aircraft noise, which is associated with various adverse health effects, with noise annoyance being among the most prevalent. This study identifies acoustic and psychoacoustic metrics best suited to predict noise annoyance from single aircraft flyby events. Data from four laboratory listening experiments involving 151 participants were re-analyzed for that purpose. The underlying experiments included synthesized and measured sound signals comprising a wide range of aircraft, specifically civil jet aircraft (current and future designs), helicopters, and propeller aircraft. Acoustic and psychoacoustic parameters, including effective perceived noise level, were computed to determine key predictors for annoyance. Our findings show that loudness-based indicators alone are generally adequate to predict noise annoyance effectively across diverse aircraft types. However, in the case of outliers regarding noise annoyance, adding psychoacoustic parameters, particularly tonality, roughness, and fluctuation strength, significantly improved prediction accuracy. Despite utilizing an older loudness model, the effective perceived noise level consistently exhibited excellent predictive performance, demonstrating its robustness as a baseline metric for assessing short-term annoyance from aircraft noise.

The next-generation aircraft noise simulation tool sonAIR was developed for the precise prediction of single flights and for acoustic optimisation of noise abatement flight procedures. As the tool is also capable to calculate complex scenarios such as yearly air operations, it may be used for noise mapping. This study evaluates different versions of the sonAIR aircraft noise model, each employing distinct input data and calculation settings, in comparison to each version as well as to the current FLULA2 model as a representative best-practice model. The analysis focuses on annual aircraft noise scenarios at Geneva Airport for the year 2017. The calculations reveal that sonAIR’s physics-based ground effect model introduces more local variability, resulting in less smooth noise contours but expected increased accuracy, especially when incorporating detailed ground properties. On average, however, the two models yield equivalent results. Further, while accounting for buildings improves local noise estimations through incorporating shielding effects, this adds complexity and substantial computational effort, making it suitable for specific investigations but impractical for large-scale noise mapping. Finally, meteorological effects reduce noise exposure close to the airport during daytime due to acoustic shadow zones, but double computational time, further constraining large-scale applicability. Additional calculations at Geneva Airport for a different year, for two operational years at Zurich Airport and for a hypothetical, idealized airport confirm the generalizability of these findings. The current results thus suggest to use sonAIR with detailed ground properties for general noise mapping, but to consider buildings and meteorological effects in the calculations for specific cases only.

Residential perimeter blocks can shield traffic noise, but the acoustical quality may be sub-optimal in the inner courtyards. This study investigated how effective sound-absorbing facade surfaces and balcony soffits as well as an absorbing floor (lawn) influence the acoustical quality in inner courtyards. Room acoustical simulations were carried out for eight generic and two real-world models with very large numbers of transmission paths. Facades (reflecting, fully absorbing, partially absorbing), balcony soffits (reflecting, absorbing) and courtyard floor (reflecting, absorbing) were varied. A range of room acoustical parameters were evaluated, namely, reverberation time T₂₀, early decay time EDT, strength G, speech transmission index STI, and Dietsch’s echo criterion EK. The simulations revealed that fully absorbing facades are an effective measure to improve the acoustical quality in inner courtyards, while partially absorbing facades result in smaller improvements. In fact, each additional storey of absorbing facades further improves the situation. In the case of non-absorbing facades, absorbing balcony soffits or an absorbing floor in the inner courtyard are not very effective as individual measures and may even increase disturbances due to echoes. The same holds true for situations with absorbing facades. Their feasibility should therefore be clarified for the individual situation in question.

Noise from unmanned aerial vehicles, commonly referred to as “drones,” will likely shape our acoustic environment in the near future. Yet, reactions of the population to this new noise source are still little explored. The objective of this study was to investigate short-term noise annoyance reactions to drones in a controlled laboratory experiment. Annoyance to (i) two quadcopters of different sizes in relation to common contemporary transportation noise sources (jet aircraft, propeller aircraft, helicopters, single car passbys), and (ii) different drone maneuvers (takeoff; landing; high, medium, and low flybys) flown at different speeds and elevations was systematically assessed. The results revealed that, at the same sound exposure level, drones are perceived as substantially more annoying than other airborne vehicles and passenger cars. Furthermore, for drone maneuvers, landings, and takeoffs are more annoying than flybys, as are maneuvers flown at low speed. Different loudness metrics (LAE, LDE, effective perceived noise level, psychoacoustic loudness level) accounted for drone noise annoyance ratings to an equal degree. An analysis of psychoacoustic parameters highlighted the significant link between drone noise annoyance and tonality, sharpness, and loudness level. The results suggest a different perception and an increased annoyance potential of drones, which will likely require specifically tailored legislation.