The effect of traffic at speed bumps in residential areas on noise and air pollution

• Published in: Environmental science and pollution research international Vol. 30; no. 33; pp. 80945 - 80962
• Main Author: AlKheder, Sharaf
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2023; Springer Nature B.V
• Subjects: Air Pollutants - analysis; Air pollution; Air Pollution - analysis; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Decibels; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Exposure - analysis; Environmental factors; Environmental Health; Environmental Monitoring - methods; Environmental science; Heavy vehicles; Humans; Internal combustion engines; Mathematical models; Noise; Noise levels; Noise pollution; Noise prediction; Particulate matter; Particulate Matter - analysis; Regression models; Research Article; Residential areas; Road humps; Statistical analysis; Statistical models; Sulfur; Sulfur dioxide; Surveys; Traffic flow; Traffic models; Transportation systems; Waste Water Technology; Water Management; Water Pollution Control; Kuwait; Speed bumps; Air pollution; Survey; Multivariate linear regression model; Traffic flow; Noise
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-28187-4

Although transportation systems are an increasing necessity in today’s connected world, the over-reliance on internal combustion engine vehicles has caused an increase in air and noise pollution. Air and noise pollutions are among the negative environmental factors that contribute to disease occurrence due to their negative health consequences. Literature has showed that air and noise pollutions were responsible for thousands of premature deaths in Europe. This has pushed scientists to search for models to calculate the effect of traffic on air and noise pollution, to help predict future scenarios, and to work on ways to mitigate that increase in pollution. In this paper, a statistical model is done by using data measured for 25 speed bump locations in Kuwait, which included traffic flow data in the form of vehicle count and classification, as well as noise level measurements taken through an Amprobe SM20 sound meter, in addition to air pollutant data obtained from the Environment Public Authority (EPA) in Kuwait. The results of the multivariate linear regression model showed that high traffic counts resulted in significantly higher noise levels, reaching more than 70 decibels in certain locations, which is considered unhealthy for extended time periods. The model also showed that sulfur dioxide levels were impacted by both light and heavy vehicles, while particulate matter less than 10 µm was affected mainly by heavy vehicles. An online survey on speed bumps was completed by 803 participants to understand the behavior of people at speed bumps in Kuwait and understand if age and gender might be a predictor of how people would behave, and this was done by doing Pearson’s chi-squared correlation tests on the results obtained from the survey.