Noise Mapping and Impact of COVID-19 Lock Down on Traffic Noise Induced Health Issues Using SEM Approach

Abstract

The COVID-19 pandemic has had profound global repercussions, leading to substantial fatalities and economic losses worldwide. However, amidst these adversities, the pandemic inadvertently offered a unique opportunity to assess the impact of reduced human activity on environmental noise levels. This study focuses on monitoring and mapping noise pollution levels at 101 locations managed by the Bhubaneswar Development Authority (BDA) in Bhubaneswar, Odisha, India, during three distinct periods: pre-COVID, during COVID-lockdown, and post-COVID. Using ArcGIS 10.2.1, noise data are spatially analysed across different zones designated by the Central Pollution Control Board (CPCB), namely Industrial, Commercial, Residential, and Silence Zones. The findings reveal a significant reduction in traffic noise during the COVID-19 lockdown period compared to both pre-COVID and post-COVID periods across all four zones. To assess the potential impact on human health, the study employs equations developed by Miedema and Vos (Acoust Soc Am 104:3432–3445, 1998, https://doi.org/10.1121/1.423927) for calculating percentages of highly annoyed individuals and estimating sleeping disorders. Additionally, Structural Equation Modeling (SEM) is applied to explore associations between noise levels and health outcomes across different time periods. Despite the significant reduction in traffic noise observed during the COVID-19 lockdown, our analysis suggests that this decrease did not have a statistically significant effect on annoyance levels (p-value: 0.0542) or sleeping disorders (p-value: 0.121). This study provides valuable insights into the unintended consequences of urban lockdowns on environmental noise pollution and their potential implications for public health and urban planning.