Temporal and regional change of some air pollution parameters in Bursa

Çetin M., Onac A. K., Sevik H., Sen B.

Air Quality, Atmosphere and Health, vol.12, no.3, pp.311-316, 2019 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 12 Issue: 3
  • Publication Date: 2019
  • Doi Number: 10.1007/s11869-018-00657-6
  • Journal Name: Air Quality, Atmosphere and Health
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.311-316
  • Keywords: Air quality, CO 2, Noise, Particulate matter
  • Ondokuz Mayıs University Affiliated: No


Air pollution is one of the most important problems that modern urban life brings nowadays. Every year, thousands of people are affected by air pollution and it even causes deaths. There are certain places and hours that the air pollution is more intense in the cities, which is especially problematic for people with various health problems and this situation affect people’s quality of life negatively. For this reason, measuring regional and temporal changes of air pollution by scientific studies will guide the determination of the precautions to avoid negative effects of air pollution on people’s health. The purpose of this study is to evaluate the air quality based on CO 2 amount and amount of particulate matter in 6 different dimensions (0.3-μm, 0.5-μm, 1.0-μm, 2.5-μm, 5.0-μm, and 10.0-μm dimensions), and to determine the change in sound level on a regional basis depending on the time of day and the season in different areas of Bursa city center. The results of the study showed that the effect of season on noise and CO 2 was statistically insignificant, but the particulate matter dimensions are affected at statistically 99.9% confidence level by season. On the other hand, results of the analyses held during the study showed that time factor affects all parameters except noise parameter and the amount of large size (5 and 10); and the place factor effects all the parameters except the amount of particulate matter of size 2.5 and 5.0. The location season time factor was found to be effective at 99.9% confidence level over all parameters.