| dc.description.abstract | Addressing the global concern of noise
pollution emanating from urban motor traffic, this
study employed a sound model to assess the noise
landscape in the Ratnapura Municipal Council area of
Sri Lanka. Field observations provided crucial data
on vehicle speed, type, and density at various points
within the study area, serving as input for the sound
model. Data collection spanned two distinct periods,
7:00 a.m. to 9:00 a.m. and 12:30 p.m. to 2:30 p.m.,
strategically chosen to capture peak noise levels.
Utilizing multiple interpolation techniques, decibel
values were extrapolated, with the Kriging-Spherical
technique identified as the optimal method based on
field-observed noise readings at corresponding
locations. The study reveals zones within the
municipality experiencing elevated noise pollution
levels, and regional distribution maps illustrate the
intricate relationships between contributing factors
and noise pollution. The findings provide
recommendations for mitigating noise pollution, with
a specific focus on the Ratnapura context. Moreover,
this study underscores the importance of adapting
strategies
to the dynamic nature of urban
environments, enhancing our comprehension of the
current state of noise pollution. The findings provide
practical insights for governments and urban
planners, offering sustainable solutions to address this
pervasive issue. Additionally, it emphasizes the
necessity for continuous, long-term research to
comprehensively grasp evolving noise patterns,
supporting ongoing data collection and analysis
initiatives. | en_US |
