Urban noise pollution poses significant challenges to public health and environmental sustainability, particularly in rapidly developing tourist destinations. Noise pollution and associated annoyance level in five major intersections of Cox's Bazar City, Bangladesh, was assessed in this study during the peak tourist season. Noise measurements were conducted using various indices (L10, Leq, and TNI) across morning, midday, and afternoon time slots. TNI scores were compared with Mean Dissatisfaction Score (MDS) standards to assess traffic-induced noise annoyance levels. Additionally, a survey of 675 respondents was conducted to assess their perceptions of noise pollution. Statistical analyses included linear regression for noise indices, multinomial logistic regression for TNI-related dissatisfaction, and ordinal logistic regression for respondents' perceived annoyances. Results revealed significant noise pollution issues, with Leq scores consistently exceeding national guidelines across all intersections and time periods, particularly on weekends during afternoon timeslots. TNI values frequently surpassed standard dissatisfaction regulations, with 19 out of 105 time slots exhibiting extreme dissatisfaction levels. Link Road and Kolatoli Circle intersections consistently showed higher noise levels and dissatisfaction. Over 95% of survey respondents perceived increased noise pollution during peak tourist seasons, with 87.11% describing it as "extremely" or "very" noisy. Longer exposure duration and awareness of health risks were significantly associated with reported perceived annoyance levels. Respondents reported various health impacts, including annoyance (84.44%), headaches (62.37%), and cognitive impairment (44.44%). This comprehensive study provides valuable insights for policymakers, city planners, and environmentalists to develop sustainable urban strategies that balance the acoustic environment with the well-being of residents and tourists alike.
Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22-254%), while Khulna experienced the largest increase in sparse vegetation (2-124%). Dense vegetation loss was highest in Dhaka (20-77%) and water bodies (9-59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.
The desire to increase resource management efficacy in the construction sector is expanding because of measures to reduce costs, boost productivity, and minimize environmental impact. The Internet of Things (IoT) has the potential to alter resource management in the construction sector by delivering real-time data and insights that may assist decision-makers in optimizing resource allocation and usage. Incorporating Internet of Things (IoT) technology into the construction sector will be investigated in this study to discover how resource management is affected. The aim of the study is to identify the essential aspects that promote optimal IoT integration and to investigate how IoT may influence resource management. The relations between variables and their fundamental elements are investigated using structural equation modelling (SEM). In the context of building projects, the study analyses how IoT integration influences resource allocation and utilization, real-time monitoring, and proactive maintenance. The building sector in Malaysia provides concepts on IoT in resource management. Based on this research's outcomes, there is a distinct association between the utilization of IoT technology and effective resource management in the construction sector. IoT adoption is affected by a multiplicity of issues, including data analytics, data security and privacy, integration and interoperability, scalability, and flexibility. This study contributes to addressing considerable gaps in the corpus of information on IoT technology integration in the construction sector. It analyses how IoT may effect resource management, emphasizing how IoT technology may enhance the efficacy of human, mechanical, and material resources.