AI Summary & Key Takeaways
AI InsightIt may therefore be safely concluded that school children in the subject schools being exposed to the same levels of hazard as the residents in the immediate vicinity were probably suffering from similar problems.
📌 3 Key Takeaways
Abstract
This study was conducted of traffic noise which affected on urban traffic noise of selected roadside school as acoustic comfort for selected locations (near school buildings) of Burdwan town and the ambient noise was recorded during four different time periods (early morning, late morning, afternoon and evening). Geographical Information System (GIS) based Inverse distance weighting (IDW) interpolating technique was used to identify the vulnerability of noise pollution in mixed areas of schools. The different acoustic descriptor such as Leq, L90, L50, L10, noise climate (NC), traffic noise index (TNI) and noise pollution level (NPL) were evaluated, while a community study was also simultaneously conducted. The results revealed that the average Leq, L90, L50, L10 varied from 76.5 dB (A) to 78.6 dB (A), 58.2 dB (A) to 60 dB (A), 65.6 (A) to 67.3 dB (A) and 86.6 (A) to 94.5 dB (A), respectively. It was observed that the noise climate reached its peak in the afternoon (35.7 ± dB (A)) and was the lowest in the evening (27.8 ± dB (A)). The health data indicated that about 71% and 8% of the inhabitants near the schools were suffering from irritation and sleeping problems respectively. The similar correlation study revealed that Leq (r = 0.484, p < 0.679), L90 (r = 0.871, p < 0.327), and L50 (r = 0.507, p < 0.662) were strongly correlated with sleep disturbance. It may therefore be safely concluded that school children in the subject schools being exposed to the same levels of hazard as the residents in the immediate vicinity were probably suffering from similar problems.