Estimates of Population Highly Annoyed from Transportation Noise in the United States: An Unfair Share of the Burden by Race and Ethnicity

美国受交通噪音严重困扰的人口估计:不同种族和族裔群体承受的负担不公平

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Abstract

Transportation is one of the most pervasive sources of community noise. In this study, we used a spatially-resolved model of transportation-related noise with established transportation noise exposure-response functions to estimate the population highly annoyed (HA) due to aviation, road, and railway traffic sources in the United States. Additionally, we employed the use of the Fair Share Ratio to assess race/ethnicity disparities in traffic noise exposures. Our results estimate that in 2020, 7.8 million (2.4%) individuals were highly annoyed by aviation noise, while 5.2 million (1.6%) and 7.9 million (2.4%) people were highly annoyed by rail and roadway noise, respectively, across the US. The Fair Share Ratio revealed that Non-Hispanic Asian, Black, NHPI, and Other, and Hispanic populations were disproportionally highly annoyed by transportation noise nationwide. Notably, Hispanic populations experienced the greatest share of high annoyance from aviation noise (1.69 times their population share). Non-Hispanic Black populations experienced the greatest share of high annoyance from railway noise (1.48 times their population share). Non-Hispanic Asian populations experienced the greatest share of high annoyance from roadway noise (1.51 times their population share). Analyses at the state and Urban Area levels further highlighted varying disparities in transportation noise exposure and annoyance across different race ethnicity groups, but still suggested that Non-Hispanic White populations were less annoyed by all sources of transportation noise compared to non-White populations. Our findings indicate widespread presence of transportation noise annoyance across the US and emphasize the need for targeted source-specific noise mitigation strategies and policies to minimize the disproportionate impact of transportation noise in the US.

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