Prediction Of Noise Levels Research Articles

Derivation of network-wide surface condition corrections for rail noise modelling

Noise modelling and mapping techniques are increasingly being used to understand noise impacts to communities across large geographic areas. Rail transit noise around a network can vary considerably with factors such as track type, train speed, rail roughness/surface condition, among others. Reference source levels for a particular rolling stock type are normally derived by measurement at a particular location or locations, and applied around the network. When modelling noise network wide, it is important to understand how variable rail roughness can affect predicted noise levels at locations other than those used for measurements. With elevated guideway, it can also be difficult to access appropriate external measurement locations. This study describes a study undertaken for the Vancouver SkyTrain network using the Nord2000 rail noise prediction algorithm. Variations in rolling noise level of the order of 15 dB were identified and attributed to rail surface condition. Noise measurements inside a test train were used to determine frequency dependent train speed coefficients and corrections to apply for rail condition around the network. This paper describes the approach used and the outcomes in relation to this city-wide rail noise mapping project.

P026] Dose and image quality evaluation in computed tomography with an anthropomorphic phantom

Purpose Clinical PET/CT exams include a CT for attenuation correction and anatomical localization. The purpose of this study is to: • Evaluate if an anthropomorphic phantom is suitable to mimic clinical conditions regarding CT automated current modulation behaviour. • Describe the variation of the image noise as a function of reference mAs in the phantom, in order to predict noise level in clinical patients. Methods CT scans were performed with a 64-slice Somatom Definition AS CT mounted in a Biograph mCT TrueV PET/CT system, with 120 kV, 0.5 s rotation time, pitch 1 and automated current modulation. A sample of 94 patients scanned with our PET/CT clinical protocol (80 reference mAs) was reviewed. Patients similar to the “standard-man” were selected (N = 18, men with weigh 65–75 kg). The parameters of the CT exploration (effective mAs and CTDIvol) were registered. An anthropomorphic phantom (3D Torso Phantom, CIRS) was scanned with different reference mAs. Effective mAs and CTDIVol were recorded. Several circular regions of interest were drawn in lung, bone and soft tissue. Noise was quantified as the mean of standard deviation in Hounsfield Units (HU). Results Clinical CT for the “standard-man” was acquired with 49.5 ± 5.7 effective mAs and CTDIvol of 3.62 ± 0.4 mGy. When the CIRS phantom was scanned with 80 reference mAs, 45 effective mAs and a CTDIvol of 3.28 mGy were produced. One-sample t-test showed statistically significant differences between the patients sample and the phantom (p Noise measured in the phantom with 80 reference mAs was 41.9 HU in bone, 15.2 HU in lung and 22.6 HU in soft tissue. When reference mAs varied from 10 to 120 mAs, noise in lung, bone and soft tissue varied as a potential function of effective mAs with R2 greater than 0.94. Conclusions There is no concordance between the anthropomorphic phantom and the clinical studies. A function to model the relation between effective mAs and noise has been determined with a good fit.

Noise Prediction in Industrial Workrooms Using Regression Modeling Methods Based on the Dominant Frequency Cutoff Point

Noise pollution is one of the major problems in industrial environments. The physiological response to the noise in industrial environments depends on the characteristics of the noise and environment. This study aimed to develop an empirical model for predicting the level of noise in closed industrial spaces using regression modeling based on the dominant frequency cutoff point. After identifying and determining the effective input variables in the prediction of noise level, the relevant data were collected from 56 industrial workrooms and the model was developed using multiple regression technique. The two models were best fitted to estimate the noise level for workrooms with a dominant frequency of less or equal to and more than 250 Hz (R2 = 0.86, R2 = 0.85, respectively). Based on the results of this study, it is less costly and requires less equipment for noise evaluation and monitoring by the mentioned models during the design, implementation, and operation of industrial environments. These experimental models can be used as suitable measures for screening closed industrial spaces and ranking them in terms of the amount of noise pollution.

Computing MDR-Game with Applications to Real Data

Originally developed for probability and statistic purposes, Multiple Dice Rolling (MDR) game turns out to be useful for many other applications such as complex biological systems and medical research. It has been mainly used to estimate system states that cannot be observed directly. MDR game is affected by noise and fluctuations. It is widely agreed that noise in dynamic systems is captured by using the available computational and experimental technics, which provide information on the dynamics, size and entropy. Recently, computational advances have used algorithmic strategies and focused on stochastic accuracy to predict noise level in a given systems. It is known that experimental techniques can fully characterized the noise pattern and in some cases predicted relatively good outcomes for the MDR game. In this research, we developed a stochastic theory based on the MDR game and applied real data from to the Ciona and Beer-Tavazoie datasets. We found that the Ciona data (cell biometry) was relatively stable and the Beer-Tavazoie data (gene expression) was noisy. These facts support the well-known biologists’ theories that “cells are stable, but genes which are components of cells are unstable”. Furthermore, we have, for the first time, demonstrated quantitatively the molecular biology dogma. This result can be further developed in a novel direction to further understand the disease prediction, control and aging monitoring at the molecular and genetic levels.

An adaptive grid to improve the efficiency and accuracy of modelling underwater noise from shipping

Underwater noise pollution from shipping is a significant ecological concern. Acoustic propagation models are essential to predict noise levels and inform management activities to safeguard ecosystems. However, these models can be computationally expensive to execute. To increase computational efficiency, ships are spatially partitioned using grids but the cell size is often arbitrary. This work presents an adaptive grid where cell size varies with distance from the receiver to increase computational efficiency and accuracy. For a case study in the Celtic Sea, the adaptive grid represented a 2 to 5 fold increase in computational efficiency in August and December respectively, compared to a high resolution 1 km grid. A 5 km grid increased computational efficiency 5 fold again. However, over the first 25 km, the 5 km grid produced errors up to 13.8 dB compared to the 1 km grid, whereas, the adaptive grid generated errors of less than 0.5 dB.

Road traffic noise prediction model for heterogeneous traffic based on ASJ-RTN Model 2008 with consideration of horn

This research aimed to predict the noise produced by the traffic in the road network in Makassar City using ASJ-RTN Model 2008 by calculating the horn sound. Observations were taken at 37 survey points on road side. The observations were conducted at 06.00 - 18.00 and 06.00 - 21.00 which research objects were motorcycle (MC), light vehicle (LV) and heavy vehicle (HV). The observed data were traffic volume, vehicle speed, number of horn and traffic noise using Sound Level Meter Tenmars TM-103. The research result indicates that prediction noise model by calculating the horn sound produces the average noise level value of 78.5 dB having the Pearson’s correlation and RMSE of 0.95 and 0.87. Therefore, ASJ-RTN Model 2008 prediction model by calculating the horn sound is said to be sufficiently good for predicting noise level.

Wayside noise measurement and propagation predictions for four motorcycles categories

Motorcycle noise is distinct from other types of road transportation noise and it varies within this general vehicle type based on design characteristics. One-third octave band sound levels that had been measured for four motorcycles categories (cruiser, sport, dual purpose, and touring) using statistical, isolated pass-by techniques for wayside measurements were analyzed. The spectra are dominated by different frequency components depending on the category and these differences have implications on how sound for different categories propagates over extended distances. This is an important consideration for predicting and mitigating motorcycle noise. To illustrate this, these measurements were used to modify a version of the Federal Highway Administration's Traffic Noise Model. This model was then used to predict noise levels at various distances representative of typical receptor locations for the different motorcycle categories. It is expected that accounting for these differences will aid local, state and federal agencies that wish to improve the management of motorcycle noise in their jurisdictions.

Leading-Edge Noise Prediction of General Airfoil Profiles with Spanwise-Varying Inflow Conditions

This paper presents a study of the leading-edge noise radiated by an airfoil undergoing a turbulent inflow. The noise prediction of generic airfoil profiles subjected to spanwise-varying inflow conditions is performed with the support of Amiet’s theory and the inverse strip technique. In the proposed methodology, the aeroacoustic transfer function of a generic airfoil profile is computed by the boundary element method. The effects of the airfoil leading-edge thickness on the inflow turbulence are accounted for by a turbulence spectrum based on the rapid distortion theory. This research shows that the turbulence distortion plays a significant role on the predicted noise levels. Compared with the von Kármán model for isotropic turbulence, the rapid distortion theory predicts reduced noise levels at high frequencies and increased noise levels at low frequencies. This paper also shows that the spanwise-varying inflow, here represented by a linearly changing condition, contributes to raising the noise levels when compared to the similar uniform inflow case. This research confirms that the finite airfoil thickness decreases the airfoil-gust lift response, consequently reducing the noise levels. This observation is more pronounced for microphones positioned downstream of the airfoil and for high frequencies.

WHO Environmental Noise Guidelines for the European Region: A Systematic Review on Environmental Noise and Effects on Sleep.

To evaluate the quality of available evidence on the effects of environmental noise exposure on sleep a systematic review was conducted. The databases PSYCINFO, PubMed, Science Direct, Scopus, Web of Science and the TNO Repository were searched for non-laboratory studies on the effects of environmental noise on sleep with measured or predicted noise levels and published in or after the year 2000. The quality of the evidence was assessed using GRADE criteria. Seventy four studies predominately conducted between 2000 and 2015 were included in the review. A meta-analysis of surveys linking road, rail, and aircraft noise exposure to self-reports of sleep disturbance was conducted. The odds ratio for the percent highly sleep disturbed for a 10 dB increase in Lnight was significant for aircraft (1.94; 95% CI 1.61–2.3), road (2.13; 95% CI 1.82–2.48), and rail (3.06; 95% CI 2.38–3.93) noise when the question referred to noise, but non-significant for aircraft (1.17; 95% CI 0.54–2.53), road (1.09; 95% CI 0.94–1.27), and rail (1.27; 95% CI 0.89–1.81) noise when the question did not refer to noise. A pooled analysis of polysomnographic studies on the acute effects of transportation noise on sleep was also conducted and the unadjusted odds ratio for the probability of awakening for a 10 dBA increase in the indoor Lmax was significant for aircraft (1.35; 95% CI 1.22–1.50), road (1.36; 95% CI 1.19–1.55), and rail (1.35; 95% CI 1.21–1.52) noise. Due to a limited number of studies and the use of different outcome measures, a narrative review only was conducted for motility, cardiac and blood pressure outcomes, and for children’s sleep. The effect of wind turbine and hospital noise on sleep was also assessed. Based on the available evidence, transportation noise affects objectively measured sleep physiology and subjectively assessed sleep disturbance in adults. For other outcome measures and noise sources the examined evidence was conflicting or only emerging. According to GRADE criteria, the quality of the evidence was moderate for cortical awakenings and self-reported sleep disturbance (for questions that referred to noise) induced by traffic noise, low for motility measures of traffic noise induced sleep disturbance, and very low for all other noise sources and investigated sleep outcomes.

Noise level prediction in a bakery using panel contribution analysis combined with scale modeling

Panel contribution analysis combined with scale modeling was utilized to determine the sound pressure level at different positions in a bakery. The primary sources of noise were three heating and air conditioning units. Each of the units was discretized into several patches and the volume velocity for each patch was measured. Transfer functions were measured between the patches and two different customer locations for the full-scale baseline case and using a 1/10 scale model. Transfer functions for the scale model were adjusted to account for air attenuation in the full-scale case. Panel contribution analysis was used to predict noise levels assuming both correlated and uncorrelated sources. Predicted results compared well with measurement. The suggested method can be used to assess the sound pressure levels in large interior spaces before they are constructed so long as the source positions are known. In addition, contributions from the individual sources can be assessed and ranked.

Machine learning for spatial interpolation of noise monitor levels

Continuously recording noise monitoring stations provide feedback of the noise environment at monitor locations. While this feedback is useful, it only provides information at a few point locations and, in many cases, it is of interest to know the noise level(s) at locations between and beyond noise monitoring locations. In this study, we test several machine learning models (e.g., random forests, support vector machines, and neural networks) for their ability to predict noise levels using a small number of noise monitors. Unlike the hybrid geostatistical-acoustical method proposed by Nykaza [Nykaza, Ph.D. thesis, 2013] which requires knowledge of the source location, the methods proposed in this study can be trained to estimate noise levels without knowledge of the source location. The accuracy of each model is assessed with the root-mean-square-error, and we discuss the practical implications of implementing such approaches in real-time systems.

Modelling traffic noise level on roadside traders at Wurukum market area in Makurdi town, Benue state – Nigeria

Noise level prediction model was built for road side traders at an open market area of Wurukum market in Makurdi town. One week survey was carried out to measure noise level, traffic volume, vehicles speeds and distances from the edge of road shoulder. The study revealed that roadside traders expose themselves to average noise levels of 82.33dB (A), 77.48dB (A) and 74.38dB (A) at distances of 0m, 5m and 10m respectively from the edge of roadway. At 0m, the noise level was slightly below World Health Organization ( WHO ) specification of 85dB (A), beyond which noise pollution is hazardous. At 10m, the noise level was ab ove minimum safe level of 55dB (A). The model indicates high level of ambient noise which was attributed to intensive market activities from the background. The model was checked using Chi square test at 5% level of significance and coefficient of determin ation (R 2 =0.7216) which gave satisfactory results. A strategy of relocation and splitting the market was proposed for local government council’s consideration. Key words : Wurukum Market, Ambient noise, Traffic noise, safe noise threshold, roadside traders .

A novel channel state prediction technique for overlay cognitive radio-based emergency sensor networks

For overlay cognitive radio (CR), this paper proposes a knowledge-based spectrum prediction technique using artificial neural network. This is targeted for CR-based emergency sensor networks in real life applications, where extremely reliable data transmission is mandatory. The technique operates in two steps: 1) identification of idle states in primary user bands; 2) prediction of noise level of the idle bands. The goal is to select a less noisy vacant band among the detected idle bands. The system is analysed under both Gaussian mixer noise (GMN) distribution and additive white Gaussian noise (AWGN) by predicting the current state of the channel in low SNR environment. Simulation results using MATLAB R2015b show satisfactory values for probability of false alarm (0.17 and 0.3), and probability of misdetection (0.12 and 0.25) for AWGN and GMN, respectively.

A Novel Channel State Prediction Technique for Overlay Cognitive Radio-based Emergency Sensor Networks

For overlay cognitive radio (CR), this paper proposes a knowledge-based spectrum prediction technique using artificial neural network. This is targeted for CR-based emergency sensor networks in real life applications, where extremely reliable data transmission is mandatory. The technique operates in two steps: 1) identification of idle states in primary user bands; 2) prediction of noise level of the idle bands. The goal is to select a less noisy vacant band among the detected idle bands. The system is analysed under both Gaussian mixer noise (GMN) distribution and additive white Gaussian noise (AWGN) by predicting the current state of the channel in low SNR environment. Simulation results using MATLAB R2015b show satisfactory values for probability of false alarm (0.17 and 0.3), and probability of misdetection (0.12 and 0.25) for AWGN and GMN, respectively.

Novel scaling law for estimating propeller tip vortex cavitation noise from model experiment

The tip vortex cavitation (TVC) noise of marine propellers is of interest due to the environmental impacts from commercial ships as well as for the survivability of naval ships. Due to complicated flow and noise field around a marine propeller, a theoretical approach to the estimation of TVC noise is practically unrealizable. Thus, estimation of prototype TVC noise level is realized through extrapolation of the model TVC noise level measured in a cavitation tunnel. In this study, for the prediction of prototype TVC noise level from a model test, a novel scaling law reflecting the physical basis of TVC is derived from the Rayleigh-Plesset equation, the Rankine vortex model, the lifting surface theory, and other physical assumptions. Model and prototype noise data were provided by Samsung Heavy Industries (SHI) for verification. In applying the novel scaling law, similitude of the spectra of nuclei is applied to assume the same nuclei distribution in the tip vortex line of the model and the prototype. It was found that the prototype TVC noise level predicted by the novel scaling law has better agreement with the prototype TVC noise measurement than the prototype TVC noise level predicted by the modified ITTC noise estimation rule.

Acceptable Noise Levels for Typical Outdoor Leisure Activities

Throughout the Appalachian Mountain chain, entrepreneurs have capitalized on the outdoor sporting experience. Both summer and winter sports such as fly fishing, hiking, skiing and snowboarding are very popular. One popular emerging activity is skeet, trap, and sporting clays shooting. Major tourist enterprises are developing this opportunity for both tourists and the local residents. To meet the increasing demand, ranges are being constructed throughout the region from Alabama to Maine. Within North Carolina that are approximately 12 ranges, with an additional 10 in east Tennessee. Although these activities have had few opponents, sporting clays establishments have received an insignificant number of complaints that the noise level is above the noxious level. A research experiment was designed to test noise levels at one sporting clays course situated near a vacation resort. The first phase of this experiment determined that the noise levels at the source from 12 and 20 gauge shotguns were insignificant. The allowable rounds used are the standard reduced load target load. At the source there was a significant difference between trap (85.85 dBA) and skeet (74.95 dBA). At the closest guest location (second phase) 333 samples were taken between August 2015 and March 2016. The noise level averaged 53.7 dBA (σ = 7.43dBA). During the third phase (January to March 2016) 44 samples were obtained at the main resort lodging site. At Site 2 the noise level averaged 31.9 dBA (σ = 5.45). The fourth and final phase of this study was to determine the noise levels at the closest guest location for each of the 12 sporting clays stations. Ninety-six samples (8 per station) were collected in October 2016. The average noise level was 53.0 dBA (σ 4.19 dBA). An analysis at the statistical confidence level of 97.5% was conducted. First all stations were analyzed in a pairwise comparison analysis. Stations that were not significantly different from one another were combined. Thus the 12 stations were reduced to three combined stations. The analysis determined that the noise level from stations 1 through 5 (48.9dBA, σ =1.50 dBA) was significantly lower than from the other stations. Next loudest was the combinations of stations 6, 7, 10, and 11 (54.1 dBA, σ = 1.69). The last loudest combination was stations 8, 9, and 12 (58.6 dBA, σ = 1.50 dDA). Thus there was a difference of 9.7 dBA between the lowest and the loudest station. Since every 5 dBA difference equates to 2 to 3 times louder, depending on frequency, the loudest station is approximately 4 to 6 times louder that the lowest noise level. However, all stations are below the OSHA Standard. With an annoyance level (60.0 dBA) for the guest activity, the gunshots are less than the nuisance level and significantly less than the permissible level. The few complaints about the noise levels are not supported by the noise level data. A logical conclusion is that the objection is the act of shooting and not the noise level of the shotgun’s sharp or impact report. Potential solutions might be to examine stations 8, 9, and 12 and considering possible relocation, orientation, or emplacement of a thick tree barrier to absorb the reports. Regression analysis was used to develop a highly significant model to predict noise levels with the variables collected. However, this will not solve the complaints from those who object to reports under any circumstance.

Prediction of rail and bridge noise arising from concrete railway viaducts by using a multilayer rail fastener model and a wavenumber domain method

Concrete viaducts are an important part of urban rail transit systems but they produce considerable noise, thereby affecting the communities living nearby. The vibration generated at the wheel–rail interface is transmitted along the rail and also onto the bridge; hence, noise is radiated from both the rail and the bridge. To facilitate noise prediction, it is desirable to develop a model that takes into account the generation and transmission of vibration in the train–track–bridge system. The vibration and the associated noise of the track–bridge system are computed with a unified vibroacoustic model using a wavenumber domain finite element and boundary element method. An important aspect to note is the frequency-dependent stiffness of a typical rail fastener utilized on bridges due to the resonance of the baseplate between the two rubber pads. In this study, to allow for this effect, a multilayer fastener model is proposed. The proposed procedure is applied to a viaduct with a U-shaped section and compared with field measurements during the passage of trains. The elastic modulus and damping of the rubber pads and the equivalent loss factor of the rail are chosen by fitting the calculated track decay rates to those estimated from the measured rail accelerations under train passages. The wheel–rail combined roughness is also derived from the measured rail vibration. A comparison is then made between the simulated and measured bridge vibration to verify the proposed method as well as the parameters used in the track–bridge system. The predicted noise levels are also compared with the measured results. The effects of the fastener model, fastener stiffness, bridge damping, and interference between multiple wheels are then discussed. It has been found that the bridge noise has a non-negligible effect on the total A-weighted noise levels in the region beneath the bridge and up to 30 m away from the track.

Detection and Characterization of Pulses in Broadband Seismometers

Abstract Pulsing—caused either by mechanical or electrical glitches, or by microtilt local to a seismometer—can significantly compromise the long‐period noise performance of broadband seismometers. High‐fidelity long‐period recordings are needed for accurate calculation of quantities such as moment tensors, fault‐slip models, and normal‐mode measurements. Such pulses have long been recognized in accelerometers, and methods have been developed to correct these acceleration steps, but considerable work remains to be done in order to detect and correct similar pulses in broadband seismic data. We present a method for detecting and characterizing the pulses using data from a range of broadband sensor types installed in the Global Seismographic Network. The technique relies on accurate instrument response removal and employs a moving‐window approach looking for acceleration baseline shifts. We find that pulses are present at varying levels in all sensor types studied. Pulse‐detection results compared with average daily station noise values are consistent with predicted noise levels of acceleration steps. This indicates that we can calculate maximum pulse amplitude allowed per time window that would be acceptable without compromising long‐period data analysis.

Social benefit analysis of reduced noise from electrical city buses in Gothenburg

The city of Gothenburg is the second largest city in Sweden and has an ambitious traffic strategy to increase the share of public transport substantially until 2035. At the same time the city is growing due to urbanization and the densification of the city leads to an anticipated growth in city bus traffic. However, noise from buses might lead to negative consequences for the citizens and electrical buses could be a way to reduce noise and emissions from the public transport system. In this study a comparison of noise levels and social costs of bus types with different powertrains are presented. Initially, noise emissions from three bus types were measured on a test track. The propulsion noise was extracted and coefficients for the Nord2000 Road prediction model were adapted. The Nord2000 model was used to calculate facade noise levels in the city center, as well as in a smaller focus area. The predicted noise levels were used to calculate health effects according to DALYs, as well as social costs according to ASEK. In addition, indoor maximum noise levels were calculated for typical facade cases based on the measurements. The results show that the largest benefits from electrical buses are obtained during acceleration, for example, at bus stops, and for maximum levels indoors. However, these situations are not taken appropriately into account in current social cost models.The city of Gothenburg is the second largest city in Sweden and has an ambitious traffic strategy to increase the share of public transport substantially until 2035. At the same time the city is growing due to urbanization and the densification of the city leads to an anticipated growth in city bus traffic. However, noise from buses might lead to negative consequences for the citizens and electrical buses could be a way to reduce noise and emissions from the public transport system. In this study a comparison of noise levels and social costs of bus types with different powertrains are presented. Initially, noise emissions from three bus types were measured on a test track. The propulsion noise was extracted and coefficients for the Nord2000 Road prediction model were adapted. The Nord2000 model was used to calculate facade noise levels in the city center, as well as in a smaller focus area. The predicted noise levels were used to calculate health effects according to DALYs, as well as social costs accordi...

Assessing the risk of chronic shipping noise to baleen whales off Southern California, USA

ESR Endangered Species Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials ESR 32:153-167 (2017) - DOI: https://doi.org/10.3354/esr00797 Theme Section: 21st century paradigms for measuring and managing the effects of anthropogenic ocean noise Assessing the risk of chronic shipping noise to baleen whales off Southern California, USA Jessica V. Redfern1,*, Leila T. Hatch2, Chris Caldow3, Monica L. DeAngelis4, Jason Gedamke5, Sean Hastings3, Laurel Henderson6, Megan F. McKenna7, Thomas J. Moore1, Michael B. Porter6 1Marine Mammal and Turtle Division, Southwest Fisheries Science Center, NOAA Fisheries, 8901 La Jolla Shores Drive, La Jolla, CA 92037, USA 2Gerry E. Studds Stellwagen Bank National Marine Sanctuary, NOAA’s National Ocean Service, 175 Edward Foster Road, Scituate, MA 02066, USA 3Channel Islands National Marine Sanctuary, NOAA’s National Ocean Service, University of California Santa Barbara, Ocean Science Education Building 514, MC 6155 Santa Barbara, CA 93106-6155, USA 4Protected Resources Division, West Coast Regional Office, NOAA Fisheries, 501 W. Ocean Blvd. Suite 4200, Long Beach, CA 90802, USA 5Office of Science and Technology, NOAA Fisheries, 1315 East-West Highway, Silver Spring, MD 20910, USA 6Heat, Light, and Sound Research, 1625 High Bluff Drive, Suite 211, San Diego, CA 92130, USA 7Natural Sounds and Night Skies Division, National Park Service, 1201 Oakridge Drive, Fort Collins, CO 80525, USA *Corresponding author: jessica.redfern@noaa.gov ABSTRACT: Low-frequency noise that is part of the acoustic environment for baleen whales has increased in many areas of the Northeast Pacific Ocean that contain whale habitat. We conducted a spatially explicit risk assessment of noise from commercial shipping to blue, fin, and humpback whale habitats in Southern California waters and explored how noise is affected by several place-based management techniques: a National Marine Sanctuary, an Area to be Avoided (ATBA), and a Traffic Separation Scheme (TSS). We used shipping data to model noise at 2 frequencies that are part of the acoustic environment for these species and capture the variable contributions from shipping to noise. Predicted noise levels in Southern California waters suggest high, region-wide exposure to shipping noise. Our risk assessment identified several areas where the acoustic environment may be degraded for blue, fin, and humpback whales because their habitat overlaps with areas of elevated noise from shipping traffic and 2 places where blue and humpback whale feeding areas overlap with lower predicted noise levels. One of the places with lower predicted noise occurs in the Channel Islands National Marine Sanctuary (CINMS). Noise has not been directly managed within the CINMS; instead, reduced noise in this portion of the CINMS is likely an ancillary benefit of the ATBA surrounding most of the Sanctuary. Areas of elevated noise in the CINMS also occur, primarily where a TSS intersects the Sanctuary’s boundaries. Our risk assessment framework can be used to evaluate how shipping traffic affects acoustic environments and explore management strategies. KEY WORDS: Anthropogenic noise · Risk assessment · Habitat modeling · Automatic Identification System (AIS) data · Commercial shipping Full text in pdf format PreviousNextCite this article as: Redfern JV, Hatch LT, Caldow C, DeAngelis ML and others (2017) Assessing the risk of chronic shipping noise to baleen whales off Southern California, USA. Endang Species Res 32:153-167. https://doi.org/10.3354/esr00797 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in ESR Vol. 32. Online publication date: February 23, 2017 Print ISSN: 1863-5407; Online ISSN: 1613-4796 Copyright © 2017 Inter-Research.