TY - JOUR ID - 34908 TI - The relationships between meteorological parameters and air pollutants in an urban environment JO - Global Journal of Environmental Science and Management JA - GJESM LA - en SN - 2383-3572 AU - Kayes, I. AU - Shahriar, S.A. AU - Hasan, K. AU - Akhter, M. AU - Kabir, M.M. AU - Salam, M.A. AD - Department of Environmental Science and Disaster Management, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh Y1 - 2019 PY - 2019 VL - 5 IS - 3 SP - 265 EP - 278 KW - Air pollution KW - Humidity KW - PM2.5 and PM10 KW - Regression Analysis KW - Temperature DO - 10.22034/GJESM.2019.03.01 N2 - Meteorological parameters play a significant role in affecting ambient air quality of an urban environment. As Dhaka, the capital city of Bangladesh, is one of the air pollution hotspot among the megacities in the world, however the potential meteorological influences on criteria air pollutants for this megacity are remained less studied. The objectives of this research were to examine the relationships between meteorological parameters such as daily mean temperature (o C), relative humidity (%) and rainfall (mm) and, the concentration of criteria air pollutants (SO2, CO, NOx, O3, PM2.5 and PM10) from January, 2013 to December, 2017. This study also focused on the trend analysis of the air pollutants concentration over the period. Spearman correlation was applied to illustrate the relationships between air pollutants concentration and temperature, relative humidity and rainfall.  Multiple linear and non-linear regressions were compared to explore potential role of meteorological parameters on air pollutants' concentrations. Trend analysis resulted that concentration of SO2 is increasing in the air of Dhaka while others are decreasing. Most of the pollutants resulted negative correlation with atmospheric temperature and relative humidity, however, they showed variable response to seasonal variation of meteorological parameters. Regression analysis resulted that both the multiple non-linear and linear model performed similar for predicting concentrations of particulate matters but for gaseous pollutants both model performances were poor. This research is expected to contribute in improving the forecast accuracy of air pollution under variable meteorological parameters considering seasonal fluctuations. UR - https://www.gjesm.net/article_34908.html L1 - https://www.gjesm.net/article_34908_c34418e18e8ee7aa9cac4245a9987f04.pdf ER -