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Article: Automated simulation for household road traffic noise exposure: Application and field evaluation in a high-density city
| Title | Automated simulation for household road traffic noise exposure: Application and field evaluation in a high-density city |
|---|---|
| Authors | |
| Keywords | Environmental burden of disease High-density city Household noise exposure Road traffic noise Simulation |
| Issue Date | 1-Sep-2023 |
| Publisher | Elsevier |
| Citation | Computers, Environment and Urban Systems, 2023, v. 104 How to Cite? |
| Abstract | Road traffic noise is a major nuisance and a risk factor of poor health for urban dwellers. A household's exposure to road traffic noise, especially in a high-density city, can be easily modified by the surrounding built environment, i.e., roads, traffic, buildings, and the topography. This leads to high variation in noise exposure between neighboring households. Existing simulation-based studies were limited in accounting for the variation of noise exposure at the household level, which restricted their applications in public health research involving large numbers of participants. This paper describes a novel simulation-based workflow to assess household traffic noise exposure, which consists of 1) a source model to assess road traffic noise levels, 2) a propagation model to simulate noise propagation in complex three-dimensional urban areas, 3) an automation algorithm to process large quantity of simulation runs and data. The workflow has been evaluated using field studies conducted in Sham Shui Po District, Hong Kong, with reasonably good agreements between simulated and measured data. It was then used to assess road traffic noise exposure for a sample of 6158 households enrolled in the FAMILY Cohort, representing Hong Kong's population dwelling in the dense urban areas. Results showed that 83% of sampled households have been exposed to excessive road traffic noise above the World Health Organization (WHO) standard, or 30% above the local standard. The estimated burden of disease is over 45,000 disability-adjusted life-years (DALYs) from both high annoyance and sleep disturbance for households in Hong Kong. The study has contributed to the methodologies and datasets in evaluating noise exposure in high-density cities, which can further support urban noise mitigation policies and planning and population-based health studies in the next steps. |
| Persistent Identifier | http://hdl.handle.net/10722/333931 |
| ISSN | 2023 Impact Factor: 7.1 2023 SCImago Journal Rankings: 1.861 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Guo, Mengdi | - |
| dc.contributor.author | Ni, Michael Yuxuan | - |
| dc.contributor.author | Shyu, Rong Juin | - |
| dc.contributor.author | Ji, John | - |
| dc.contributor.author | Huang, Jianxiang | - |
| dc.date.accessioned | 2023-10-10T03:14:30Z | - |
| dc.date.available | 2023-10-10T03:14:30Z | - |
| dc.date.issued | 2023-09-01 | - |
| dc.identifier.citation | Computers, Environment and Urban Systems, 2023, v. 104 | - |
| dc.identifier.issn | 0198-9715 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/333931 | - |
| dc.description.abstract | <p>Road traffic noise is a major nuisance and a risk factor of poor health for urban dwellers. A household's exposure to road traffic noise, especially in a high-density city, can be easily modified by the surrounding built environment, i.e., roads, traffic, buildings, and the topography. This leads to high variation in noise exposure between neighboring households. Existing simulation-based studies were limited in accounting for the variation of noise exposure at the household level, which restricted their applications in <a href="https://www.sciencedirect.com/topics/social-sciences/public-health-research" title="Learn more about public health research from ScienceDirect's AI-generated Topic Pages">public health research</a> involving large numbers of participants. This paper describes a novel simulation-based workflow to assess household traffic noise exposure, which consists of 1) a source model to assess road traffic noise levels, 2) a <a href="https://www.sciencedirect.com/topics/computer-science/propagation-model" title="Learn more about propagation model from ScienceDirect's AI-generated Topic Pages">propagation model</a> to simulate <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/noise-propagation" title="Learn more about noise propagation from ScienceDirect's AI-generated Topic Pages">noise propagation</a> in complex three-dimensional urban areas, 3) an automation algorithm to process large quantity of simulation runs and data. The workflow has been evaluated using field studies conducted in Sham Shui Po District, Hong Kong, with reasonably good agreements between simulated and measured data. It was then used to assess road traffic noise exposure for a sample of 6158 households enrolled in the FAMILY Cohort, representing Hong Kong's population dwelling in the dense urban areas. Results showed that 83% of sampled households have been exposed to excessive road traffic noise above the World Health Organization (WHO) standard, or 30% above the local standard. The estimated burden of disease is over 45,000 disability-adjusted life-years (DALYs) from both high annoyance and <a href="https://www.sciencedirect.com/topics/computer-science/sleep-disturbance" title="Learn more about sleep disturbance from ScienceDirect's AI-generated Topic Pages">sleep disturbance</a> for households in Hong Kong. The study has contributed to the methodologies and datasets in evaluating noise exposure in high-density cities, which can further support <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/urban-noise" title="Learn more about urban noise from ScienceDirect's AI-generated Topic Pages">urban noise</a> mitigation policies and planning and population-based <a href="https://www.sciencedirect.com/topics/social-sciences/health-study" title="Learn more about health studies from ScienceDirect's AI-generated Topic Pages">health studies</a> in the next steps.<br></p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Computers, Environment and Urban Systems | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject | Environmental burden of disease | - |
| dc.subject | High-density city | - |
| dc.subject | Household noise exposure | - |
| dc.subject | Road traffic noise | - |
| dc.subject | Simulation | - |
| dc.title | Automated simulation for household road traffic noise exposure: Application and field evaluation in a high-density city | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.compenvurbsys.2023.102000 | - |
| dc.identifier.scopus | eid_2-s2.0-85162176944 | - |
| dc.identifier.volume | 104 | - |
| dc.identifier.eissn | 1873-7587 | - |
| dc.identifier.isi | WOS:001054756400001 | - |
| dc.identifier.issnl | 0198-9715 | - |