title: Assessment of traffic-related noise in three cities in the United States.
abstract: BACKGROUND
  Traffic-related noise is a growing public health concern in developing and developed countries due to increasing vehicle traffic. Epidemiological studies have reported associations between noise exposure and high blood pressure, increased risk of hypertension and heart disease, and stress induced by sleep disturbance and annoyance. These findings motivate the need for regular noise assessments within urban areas. This paper assesses the relationships between traffic and noise in three US cities.
  
  
  METHODS
  Noise measurements were conducted in downtown areas in three cities in the United States: Atlanta, Los Angeles, and New York City. For each city, we measured ambient noise levels, and assessed their correlation with simultaneously measured vehicle counts, and with traffic data provided by local Metropolitan Planning Organizations (MPO). Additionally, measured noise levels were compared to noise levels predicted by the Federal Highway Administration's Traffic Noise Model using (1) simultaneously measured traffic counts or (2) MPO traffic data sources as model input.
  
  
  RESULTS
  We found substantial variations in traffic and noise within and between cities. Total number of vehicle counts explained a substantial amount of variation in measured ambient noise in Atlanta (78%), Los Angeles (58%), and New York City (62%). Modeled noise levels were moderately correlated with measured noise levels when observed traffic counts were used as model input. Weaker correlations were found when MPO traffic data was used as model input.
  
  
  CONCLUSIONS
  Ambient noise levels measured in all three cities were correlated with traffic data, highlighting the importance of traffic planning in mitigating noise-related health effects. Model performance was sensitive to the traffic data used as input. Future noise studies that use modeled noise estimates should evaluate traffic data quality and should ideally include other factors, such as local roadway, building, and meteorological characteristics.
authors.affiliation: Division of Environmental Health Science, School of Public Health, University of California, 50 University Hall, Berkeley, CA 94720, USA. Electronic address: izeunice@gmail.com.
authors.forename: Eunice Y
authors.initials: EY
authors.lastname: Lee
authors.affiliation: Division of Environmental Health Science, School of Public Health, University of California, 50 University Hall, Berkeley, CA 94720, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Jerrett
authors.affiliation: ZevRoss Spatial Analysis, 120 North Aurora Street, Suite 3A, Ithaca, NY, USA.
authors.forename: Zev
authors.initials: Z
authors.lastname: Ross
authors.affiliation: Slone Epidemiology Center at Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, USA.
authors.forename: Patricia F
authors.initials: PF
authors.lastname: Coogan
authors.affiliation: Division of Environmental Health Science, School of Public Health, University of California, 50 University Hall, Berkeley, CA 94720, USA.
authors.forename: Edmund Y W
authors.initials: EY
authors.lastname: Seto
mesh_terms: D002947:Cities / Q000706:statistics & numerical data*; D008962:Models, Theoretical; D018986:Motor Vehicles / Q000706:statistics & numerical data*; D009622:Noise
keywords: Community noise; Noise survey; Traffic noise model; Truck traffic; Vehicle count