Noise exposure-response relationships established from repeated binary observations: Modeling approaches and applications

Road traffic noise impacts sleep continuity in suburban residents: Exposure-response quantification of noise-induced awakenings from vehicle pass-bys at night

Nocturnal traffic noise has been associated with adverse health outcomes in exposed residents. Precise quantification of traffic noise effects on sleep is thus of great importance. Here we establish an exposure-response relationship for the awakening probability due to intermittent road traffic noise in suburban residents. We conducted a field study in residential areas where road traffic was the dominant noise source, and noise events were attributable to separate vehicle pass-bys. Forty healthy participants underwent polysomnography for five consecutive nights at their homes. A total of 11,003 road traffic noises derived from simultaneous acoustic measurements at the sleepers' ears were included in an event-related analysis of awakenings. Logistic regression analysis revealed that the awakening probability due to road traffic noise increased with the maximum sound pressure level (SPL) and the maximum slope of the increasing SPL of a vehicle pass-by, as well as the age of the exposed individual. Compared to sleep stage 2, the awakening probability was higher in rapid eye movement sleep (REMS) and lower in slow wave sleep (SWS). The protective effect of both stage 2 and SWS against awakenings decreased with age, whereas no age-dependent change was observed for REMS. When adjusting for other contributing factors, the probability of a noise-induced awakening ranged from 0% at a maximum SPL of 27.1 dB(A) to 2.0% at 70 dB(A). Road traffic noise at night - even in suburban areas with moderate traffic density - negatively impacts residents' sleep continuity. Exposure-response quantification for traffic noise-induced awakenings may serve as a basis for noise protection efforts by regulators and policy makers.

Residential green is associated with reduced annoyance to road traffic and railway noise but increased annoyance to aircraft noise exposure

BACKGROUND

In recent years, residential green and availability of neighbourhood green spaces came into focus as a potential means to reduce transportation noise annoyance. Literature suggests that various characteristics of residential green may play a role, namely, greenness of the residential areas as quantified by the normalized difference vegetation index (NDVI), visible vegetation from home, and the presence of public green spaces as identified by land use classification data (LU-green), as well as their accessibility and noise pollution (i.e., transportation noise exposure within green areas, how loud/quiet they are). So far, studies mostly focused on road traffic noise in urban areas.

OBJECTIVE

We investigated the effects of residential green on noise annoyance, accounting for different transportation noise sources as well as for the degree of urbanisation.

METHODS

We complemented the data set of the recent Swiss SiRENE survey on road traffic, railway and aircraft noise annoyance with a wide range of "green" metrics, and investigated their association with annoyance by means of logistic regression analysis (generalized estimating equations).

RESULTS

Increasing residential green was found to be associated with reduced road traffic and railway noise annoyance, but increased aircraft noise annoyance. The overall effect corresponded to equivalent level reductions of about 6 dB for road traffic and 3 dB for railway noise, but to an increase of about 10 dB for aircraft noise, when residential green increased from "not much green" (5th percentile of the study sample distribution) to "a lot of green" (95th percentile). Overall, NDVI and LU-green were particularly strongly linked to annoyance. The effects of visible vegetation from home and accessibility and/or quietness of green spaces were, overall, less strong, but depended on the degree of urbanisation. For road traffic noise, visible vegetation and accessibility of green spaces seem to particularly strongly reduce annoyance in cities, while quiet green spaces are more effective in rural areas.

CONCLUSIONS

Our study emphasizes that residential green should be fostered by city planners, particularly in densely populated areas.

Bayesian statistical models for community annoyance survey data

This paper demonstrates the use of two Bayesian statistical models to analyze single-event sonic boom exposure and human annoyance data from community response surveys. Each model is fit to data from a NASA pilot study. Unlike many community noise surveys, this study used a panel sample to collect multiple observations per participant instead of a single observation. Thus, a multilevel (also known as hierarchical or mixed-effects) model is used to account for the within-subject correlation in the panel sample data. This paper describes a multilevel logistic regression model and a multilevel ordinal regression model. The paper also proposes a method for calculating a summary dose-response curve from the multilevel models that represents the population. The two models' summary dose-response curves are visually similar. However, their estimates differ when calculating the noise dose at a fixed percent highly annoyed.

Short-term annoyance reactions to civil helicopter and propeller-driven aircraft noise: A laboratory experiment

Helicopter noise exhibits distinctive acoustical characteristics (e.g., pulsation) compared to noise from propeller-driven aircraft which contains tonal components. Whereas, at comparable sound exposure levels (L_AE), annoyance reactions to these sources might be different, knowledge of potential annoyance differences is scarce. This paper reports a comparison between short-term annoyance reactions to noise from light-weight helicopters and propeller-driven aircraft in a laboratory setup. Stimuli were presented with a 3D sound reproduction system in a listening test facility based on field recordings of takeoffs and landings. Propagation filtering and amplitude changes were carried out to simulate various propagation distances and source levels, covering a reasonable L_AE range from 64 to 85 dB(A) for a stimuli length of 24 s. Fifty-six subjects rated their short-term annoyance reactions on the ICBEN 11-point numerical scale. Associations between design variables (source type, procedure, and L_AE) and short-term annoyance were explored by means of a linear mixed-effect model. L_AE was found to be the major predictor. For the major range of L_AE, no significant difference was found between annoyance to noise from the two aircraft types. Observed level differences at equal annoyance ratings were below 1 dB. Furthermore, helicopter landings were found slightly more annoying than helicopter takeoffs.